A computer-implemented method, system, and computer program product for automatically assessing text difficulty. Text reading difficulty predictions are expressed on a scale that is aligned with published reading standards. Two distinct difficulty models are provided for informational and literary texts. A principal components analysis implemented on a large collection of texts is used to develop independent variables accounting for strong intercorrelations exhibited by many important linguistic features. Multiple dimensions of text variation are addressed, including new dimensions beyond syntactic complexity and semantic difficulty. Feedback about text difficulty is provided in a hierarchically structured format designed to support successful text adaptation efforts. The invention ensures that resulting text difficulty estimates are unbiased with respect to genre, are highly correlated with estimates provided by human experts, and are based on a more realistic model of the aspects of text variation that contribute to observed difficulty variation.