Summary: Several hierarchical classes models can be considered for the modeling of three-way three-mode binary data, including the INDCLAS model [I. Van Mechelen et al., ibid. 60, No. 4, 505–521 (1995; Zbl 0864.92021)], the Tucker3-HICLAS model [E. Ceulemans et al., ibid. 68, No. 3, 413–433 (2003; Zbl 1306.62393)], the Tucker2-HICLAS model [the authors, ibid. 69, No. 3, 375–399 (2004; Zbl 1306.62391)], and the Tucker1-HICLAS model that is introduced in this paper. Two questions then may be raised: (1) how are these models interrelated, and (2) given a specific data set, which of these models should be selected, and in which rank? In the present paper, we deal with these questions by (1) showing that the distinct hierarchical classes models for three-way three-mode binary data can be organized into a partially ordered hierarchy, and (2) by presenting model selection strategies based on extensions of the well-known scree test and on the Akaike information criterion. The latter strategies are evaluated by means of an extensive simulation study and are illustrated with an application to interpersonal emotion data. Finally, the presented hierarchy and model selection strategies are related to corresponding work by H. A. L. Kiers [“Towards a standardized notation and terminology in multiway analysis”, J. Chemometrics 14, No. 3, 105–122 (1991; doi:10.1002/1099-128X(200005)] for principal component models for three-way three-mode real-valued data.