The ‘stylo’ package provides easy-to-use implementations of various established analyses in the field of computational stylistics, including non-traditional authorship attribution, genre recognition, style development (“sty-lochronometry”), etc. The package includes a number of explanatory methods provided by the function stylo() (multidimensional scaling, principal component analysis, cluster analysis, bootstrap consensus trees). Addtionally, a number of supervised machine-learning methods are available via the function classify() (Delta, support vector machines, naive Bayes, k-nearest neighbors, nearest shrunken centroids). The rolling.delta() function analyses collaborative works and tries to determine the authorship of fragments extracted from them. The function rolling.classify() offers a more flexible interface to sequential classification of collaborative works. The oppose() function performs a contrastive analysis between two given sets of texts: among other things, it generates lists of words significantly preferred and avoided by one or more authors in comparison to the texts by another author (or a set of them).