In this paper we present the results of an automatic classification of Russian texts into three levels of difficulty. Our aim is to build a study corpus of Russian, in which a L2 student is able to select texts of a desired complexity. We are building on a pitot study, in which we classified Russian texts into two levels of difficulty. In the current paper, we apply the classification to an extended corpus of 577 labelled texts. The best-performing combination of features achieves an accuracy of 0. 74.within at most one level difference.