While there is an urgent need for robust readability assessment tools, applicable to a range of communicative domains, none of the existing tools for Dutch offers a valid empirical basis and sufficient functionality. Recent developments in computational linguistics and discourse processing create possibilities to change this situation. We propose to develop a validated reading level tool, aiming at secondary school readers, adult readers of public information, and by extension, the Dutch-speaking population at large. First, a text-analytic tool is developed using the latest results of computational linguistics research. Second, cloze comprehension data are collected among secondary school readers, in a design assessing both differences between texts and between versions of the same text. Third, a subsample of texts is re-used to investigate on-line processing in eye-tracking studies. The combination of comprehension data and on-line processing measures provides insight in the way textual features affect the construction of cognitive representations. Fourth, additional cloze data are collected for adults reading government-citizen information texts in The Netherlands and Flanders. Fifth, the relation between cloze data and reading times on the one hand, and text features on the other hand, is analyzed in a multilevel regression analysis and in a machine learning study. These analyses are used to develop a reading level prediction tool: LIN (LeesbaarheidsIndex voor het Nederlands). This validated reading tool is relevant to various domains in society: education, publishing, government-citizen communication. It will provide the foundation for developing domain-specific readability and writing tools that has been missing so far.