Flesch Reading Ease

What is Flesch Reading Ease?

Flesch Reading Ease is a formula that measures how easy English text is to read. It was created by Rudolf Flesch in 1948 and scores text on a scale from 0 to 100. Higher scores mean easier text. A score of 60-70 is considered readable for most adults.^[1]

It remains one of the most widely used readability measures in content management, government communications, and SEO tools.

How is the Flesch Reading Ease score calculated?

The formula is:

Score = 206.835 - (1.015 x ASL) - (84.6 x ASW)

• ASL = Average Sentence Length (total words divided by total sentences)
• ASW = Average Syllables per Word (total syllables divided by total words)

The formula weights syllable count more heavily than sentence length. This reflects research showing that vocabulary complexity predicts reading difficulty more strongly than sentence structure.^[2]

What do the scores mean?

Score	Description	Reading level
90-100	Very Easy	5th grade
80-90	Easy	6th grade
70-80	Fairly Easy	7th grade
60-70	Standard	8th-9th grade
50-60	Fairly Difficult	10th-12th grade
30-50	Difficult	College level
0-30	Very Confusing	Graduate level

U.S. government plain language guidelines recommend scores of 60-70 for public communications. For patient-facing healthcare content, many organizations aim even higher.^[3]

What is the Flesch-Kincaid Grade Level?

The Flesch-Kincaid Grade Level is a closely related formula developed for the U.S. Navy in 1975. It uses the same inputs but maps the output to a U.S. school grade:

Grade Level = (0.39 x ASL) + (11.8 x ASW) - 15.59

This is the formula built into Microsoft Word's readability statistics. It is also the default in many SEO and content analysis tools.

Why does Flesch Reading Ease matter for large organizations?

Content teams use it to keep web content accessible to their audience. A university admissions page should score differently from a research paper. An insurance company's claims guide needs to be readable by customers, not just by adjusters.

Legal and compliance teams rely on it when regulations set readability targets. Healthcare disclosures, financial product summaries, and government notices often must meet specific reading levels. The Flesch score provides a measurable benchmark.

IT teams encounter it in content management systems. Many CMS platforms and publishing workflows flag content that falls below a set score. This gives editors a chance to revise before publishing.

For organizations with 50,000+ monthly visitors, readability affects real outcomes. Content that scores below 50 may push away visitors who cannot easily understand it. Higher readability correlates with lower bounce rates and longer time on page.

What are the limitations of Flesch Reading Ease?

It measures surface features, not understanding. A text can use short words and short sentences but still confuse readers if the topic is unfamiliar. A technical manual with brief imperative sentences can score well without being truly easy to follow.

It only works for English. The formula's constants were based on English-language text. Languages with long compound words, like Swedish, Finnish, or German, produce unreliable results without adapted versions.

It ignores layout. Dense paragraphs, small fonts, and missing headings make text harder to read. The formula cannot see any of these visual factors.

It can be gamed. Splitting long sentences in two improves the score without necessarily improving clarity. Replacing a clear technical term with a shorter but less familiar word can also inflate the score.

How is Flesch Reading Ease used in practice?

The formula works best as a screening tool, not a final verdict. It is built into:

• Microsoft Word (readability statistics)
• Yoast SEO (content analysis)
• Hemingway Editor (writing tool)
• Grammarly (writing assistant)

In content audits, teams scan every page and flag those scoring below target for editorial review. This is especially useful for large websites with thousands of pages where manual review of everything is not practical.

The score catches text that is likely too complex. But a good score does not guarantee good writing. Clarity, structure, and accuracy still require human judgment. Pairing readability scores with plain language best practices gives the strongest results.

How Askem Helps

For organizations with thousands of pages, checking readability manually is not practical. Automated content scanning tools check pages against target reading levels and flag those that fall below the threshold. Tools like Askem include Flesch-based scoring as part of continuous quality assurance. Healthcare providers, government agencies, and financial services firms can use these tools to verify that public-facing content consistently meets required reading standards. Reports can be shared with specific teams so the right editors act on the right pages.

Sources

1. Flesch, R. (1948). A new readability yardstick. Journal of Applied Psychology, 32(3), 221-233: https://psycnet.apa.org/record/1949-01274-001
2. Kincaid, J. P., Fishburne, R. P., Rogers, R. L., & Chissom, B. S. (1975). Derivation of new readability formulas for Navy enlisted personnel. Naval Technical Training Command: https://apps.dtic.mil/sti/citations/ADA006655
3. Plain Language Action and Information Network (PLAIN) — Federal Plain Language Guidelines: https://www.plainlanguage.gov/guidelines/