Readability is the ease with which a reader can understand a written text. In natural language, the readability of text depends on its content (the complexity of its vocabulary and syntax) and its presentation (such as typographic aspects that affect legibility, like font size, line height, character spacing, and line length). Researchers have used various factors to measure readability, such as:

• Speed of perception
• Perceptibility at a distance
• Perceptibility in peripheral vision
• Visibility
• Reflex blink technique
• Rate of work (reading speed)
• Eye movements
• Fatigue in reading
• Cognitively-motivated features
• Word difficulty
• N-gram analysis
• Semantic Richness

Higher readability eases reading effort and speed for any reader, but it makes a larger difference for those who do not have high reading comprehension.

Readability exists in both natural language and programming languages though in different forms. In programming, things such as programmer comments, choice of loop structure, and choice of names can determine the ease with which humans can read computer program code.

Numeric readability metrics (also known as readability tests or readability formulas) for natural language tend to use simple measures like word length (by letter or syllable), sentence length, and sometimes some measure of word frequency. They can be built into word processors, can score documents, paragraphs, or sentences, and are a much cheaper and faster alternative to a readability survey involving human readers. They are faster to calculate than more accurate measures of syntactic and semantic complexity. In some cases they are used to estimate appropriate grade level.