Ordinal data are used in a lot of domains, especially when measurements are collected from persons by observations, testings, or questionnaires. ordinalClust is an R package dedicated to ordinal data that proposes tools for modeling, clustering, co-clustering and classification. Ordinal data are modeled by the BOS distribution, which is a meaningful model parametrized by a position and a precision parameter. On one hand, the co-clustering framework uses the Latent Block Model (LBM) and an SEM-Gibbs algorithm for the parameters inference. On the other hand, the clustering and the classification methods follow on from simplified versions of this algorithm. An overview of these methods is given, and the way of using them with the ordinalClust package is described through real datasets.