Deterministic blockmodelling is a well‐established clustering method for both exploratory and confirmatory social network analysis seeking partitions of a set of actors so that actors within each cluster are similar with respect to their patterns of ties to other actors (or, in some cases, other objects when considering two‐mode networks). Even though some of the historical foundations for certain types of blockmodelling stem from the psychological literature, applications of deterministic blockmodelling in psychological research are relatively rare. This scarcity is potentially attributable to three factors: a general unfamiliarity with relevant blockmodelling methods and applications; a lack of awareness of the value of partitioning network data for understanding group structures and processes; and the unavailability of such methods on software platforms familiar to most psychological researchers. To tackle the first two items, we provide a tutorial presenting a general framework for blockmodelling and describe two of the most important types of deterministic blockmodelling applications relevant to psychological research: structural balance partitioning and two‐mode partitioning based on structural equivalence. To address the third problem, we developed a suite of software programs that are available as both Fortran executable files and compiled Fortran dynamic‐link libraries that can be implemented in the R software system. We demonstrate these software programs using networks from the literature.