Spanish Readability Analyzer: INFLESZ & Flesch-Szigriszt Test Online
What is readability and why it matters
A Spanish readability analyzer is a tool that evaluates how easily an average reader can understand a Spanish text. Unlike a spelling checker, a Spanish readability analyzer doesn't look for mistakes: it measures the structural complexity —sentence length, syllables per word, letters per word— and returns a numerical score that is interpreted through validated scales.
The readability of a text matters for three concrete reasons. In SEO, search engines tend to rank better the pages that an average visitor can read effortlessly. In accessibility, the WCAG 2.2 guidelines establish quantitative comprehension targets. In the public and healthcare sectors, plain-language guidelines require minimum readability levels for consent forms, drug leaflets and official communications addressed to citizens.
This Spanish readability analyzer computes six formulas calibrated for Spanish plus two English reference formulas, all in your browser and without sending the text to any server.
The 6 readability formulas for Spanish text
Spanish-language readability formulas are adaptations of the original Flesch formula (1948), recalibrated against Hispanic corpora. They differ in the variables they weight, in their output range and in the strength of their academic validation. Most return a score between 0 and 100; the higher the score, the easier to read. Our Spanish readability analyzer runs all of them simultaneously so you can contrast their results.
Fernández Huerta formula (1959)
The first Spanish adaptation of the Flesch index was proposed by José Fernández Huerta in 1959. His formula combines the average sentence length with the number of syllables per hundred words: FH = 206.84 − 0.60·S100 − 1.02·PF. Although its coefficients are out of date, it remains a frequently cited reference in the Spanish readability literature and is included here as a historical comparison point.
Flesch-Szigriszt formula (1993)
In his 1993 doctoral thesis at Universidad Complutense de Madrid, Francisco Szigriszt Pazos recalibrated the original Flesch coefficients against Spanish corpora, producing the Perspicuity Index: P = 206.835 − 62.3·(S/W) − (W/F). Most academic literature today recommends Flesch-Szigriszt as the most appropriate formula for Spanish readability. Its numerical value is automatically reinterpreted with the INFLESZ scale.
INFLESZ scale (Barrio-Cantalejo, 2008)
The INFLESZ scale is not an independent formula but the qualitative interpretation of the Flesch-Szigriszt score across five ranges: Very difficult (<40), Somewhat difficult (40–55), Normal (55–65), Fairly easy (65–80) and Very easy (>80). It was validated by Inés María Barrio Cantalejo and colleagues in a 2008 study published in Anales del Sistema Sanitario de Navarra, focused on healthcare texts. It is today the de facto standard for classifying readability in Spanish-speaking contexts and the primary score we display above.
Gutiérrez de Polini formula
Venezuelan researcher Luisa Elena Gutiérrez de Polini published her Comprehensibility-Readability formula in 1972, validated with school texts: CL = 95.2 − 9.7·(L/W) − 0.35·(W/F). Unlike Szigriszt, it uses letters per word rather than syllables, which makes it faster to compute but less sensitive to the phonetic particularities of Spanish. Particularly useful when working with children's texts or school material.
Crawford formula
Alan Crawford proposed in 1985 a Crawford formula that estimates the years of schooling needed to understand the text, calibrated against primary-school Spanish: Years = −0.205·OF + 0.049·SP − 3.407. It returns a numerical value interpretable as a school grade (between 1 and 17). Useful when the audience is clearly identifiable by educational level: schoolbooks, children's writing or adult literacy materials.
Mu index (Muñoz Baquedano, 2006)
The Legibilidad µ, proposed by the Muñoz Baquedano brothers in Chile in 2006, differs from the others by using the variance of word lengths: µ = (n/(n−1))·(x̄/σ²)·100. It penalizes texts with many words of the same length (artificial or list-like) and rewards those that show natural variation. As a complementary metric, the Mu index is useful when other indices give contradictory results on the same text.
How to interpret your score: table and real benchmarks
The INFLESZ scale translates the numerical output of the Spanish readability analyzer into an intuitive qualitative label. A score of 78 falls in "Fairly easy": equivalent to a general newspaper. A score of 38 falls in "Very difficult": equivalent to an official Spanish legal decree.
To understand what these values mean in practice, we have measured four representative text types from different Spanish registers. All four are available as preset examples in the tool above:
| Text type | INFLESZ | Label |
|---|---|---|
| Legal decree (BOE-style) | ~32 | Very difficult |
| Wikipedia (general entry) | ~58 | Normal |
| Sports column | ~74 | Fairly easy |
| Average tweet | ~89 | Very easy |
If you write for a general audience, a score between 65 and 80 is the reasonable target. Above 80 may sound infantilized for adult audiences. Below 55 you'll need to justify the technical complexity. For public administrations and healthcare communication, several plain-language guidelines recommend exceeding 60 as the minimum threshold. To estimate how long an average reader will take, you can complement this analysis with our word counter with reading time.
How to use our Spanish readability analyzer step by step
Using our Spanish readability analyzer is immediate and requires no registration:
- Paste your text, upload a PDF, DOCX or TXT file, or click one of the preset examples. The tool accepts documents up to 10 MB and processes everything in your browser.
- Wait for the automatic calculation. The six formulas are computed instantly, alongside two English reference formulas for comparison.
- Interpret your score. The INFLESZ label and color bar indicate which range your text falls in. Problematic sentences are highlighted in yellow (long) or red (very long or dense).
- Improve and re-measure. Apply the recommendations from the "7 techniques" section and paste the text again to see how much the score went up. You can also download a PDF report or embed your score on your own site.
All processing happens locally: neither the text nor the files you upload to the Spanish readability analyzer ever leave your browser.
7 techniques to improve readability
If your score is below the desired range, these techniques typically deliver 5- to 15-point improvements on the Flesch-Szigriszt scale without altering the message:
- Shorten sentences. Aim at a maximum of 20 words per sentence. Long sentences with multiple subordinations are usually the main drag. Split into two or three independent units.
- Use active voice. "El ministro firmó el decreto" reads faster than "El decreto fue firmado por el ministro". Passive voice adds words and forces the reader to reconstruct the subject.
- Replace polysyllabic words. "Aproximadamente" is six syllables; "cerca de" is three. Identify heavy words with our repeated words finder and substitute shorter synonyms.
- Use clear connectors. "Sin embargo", "por tanto", "en cambio" guide the reader between ideas and prevent them from having to infer the relation between successive sentences.
- Avoid multiple subordination. When a sentence contains three or more commas, it's usually overloaded. Convert each clause into a standalone sentence.
- Read aloud. If you run out of breath while pronouncing a sentence, it's too long. The fastest and most reliable test, prior to any mathematical formula.
- Iterate measurement with this Spanish readability analyzer. Don't edit blindly: paste the text, note the score, apply one change, measure again.
Who needs to measure readability?
Different professionals benefit from a Spanish readability analyzer before publishing or delivering a text:
SEO and content professionals
For SEO writers, an INFLESZ score between 65 and 80 maximizes reader retention and reduces bounce rate. A readability check inside the editorial workflow is as important as the spell checker.
Institutional communicators and public administration
Public administrations have a legal mandate to communicate in plain language. Some Spanish autonomous communities require a minimum of 60 points in their citizen-facing communications, and this kind of tool allows quantitative compliance verification.
Public healthcare
Informed consents, drug leaflets and patient-education materials must be understandable by the average patient. The INFLESZ scale was developed precisely with this use case in mind and is now an everyday metric in hospitals and health centers.
Education and publishers
School textbooks must be tuned to the target grade. The Crawford formula directly returns the equivalent years of schooling, making it possible to fit material to the corresponding age range.
Accessibility teams
WCAG 2.2 includes textual comprehension criteria. Measuring the readability of a text allows compliance verification before publishing on public websites or accessible applications.
Limitations of readability analysis
A high score does not guarantee message clarity. The formulas measure form, not content: a text can be readable and meaningless. Likewise, long proper names, acronyms and numerals written out distort the result by artificially inflating the average syllable count. Argumentative quality, paragraph cohesion and register adequacy are not measured either: perfectly scoring texts can still be confusing because of poor information structure. That's why we recommend treating what the Spanish readability analyzer returns as a first review layer, always combined with a human reading focused on the clarity of the reasoning. To shorten extensive content to its viable minimum you can also use our automatic text summarizer.
Frequently asked questions about readability
Which readability formula is best for Spanish text?
For Spanish text the most recommended formula is Flesch-Szigriszt, interpreted with the INFLESZ scale. This combination has been validated in academic studies such as Barrio Cantalejo et al. (2008) and is today the de facto standard for plain-language publications in Spanish.
What INFLESZ score should I aim for?
It depends on your audience. For a general audience aim at 65–80 (Fairly easy). For administrative texts addressed to citizens, plain-language guidelines recommend exceeding 60. Below 55 you should justify the technical complexity.
Does readability affect SEO?
Yes, but indirectly. Google does not use a readability formula as a direct ranking factor, but it does measure signals such as dwell time and bounce rate, which improve when the text is easier to read. Improving the readability of a text tends to improve ranking too.
Can I analyze a PDF directly?
Yes. Upload a PDF, DOCX or TXT file (up to 10 MB) or drag it onto the editor. All processing happens entirely in your browser: no data is sent to any server.
Does the tool work offline?
Once the page is loaded, yes. Every formula runs in local JavaScript. PDF and DOCX parsing requires the libraries to already be cached in the browser.
Can I embed my readability score on my blog?
Yes. Press the Embed button after analyzing your text. We provide two snippets: an inline-styled HTML badge with your current score and an interactive iframe. Both are free and require no forced attribution.
Start measuring your readability
Measuring the readability of a text in Spanish no longer requires installing academic software or mastering the formulas. With this Spanish readability analyzer you obtain in seconds the six metrics validated for our language, a visual interpretation through the INFLESZ scale and a highlight of the most problematic sentences. Paste your text at the top of the page and start iterating: every point your score rises is one more reader who will understand your message effortlessly.
Editorial team at Contador de Palabras. Last reviewed: . Formulas implemented after the original publications by Fernández Huerta (1959), Gutiérrez de Polini (1972), Crawford (1985), Szigriszt Pazos (1993) and Barrio-Cantalejo et al. (2008).