This chapter reviews the last decade's work on causal-based classification, the effect of interfeature causal relations on how objects are categorized. Evidence for and against the numerous effects discussed in the literature is evaluated: the causal status effect, the relational centrality effect, the multiple-cause effect, and the coherence effect. Evidence for explicit causal reasoning in classification and the work conducted on children's causal-based classification is also presented. The chapter evaluates the implications these findings have for two models of causal-based classification—the dependency model [Sloman, S. A., Love, B. C., & Ahn, W. (1998). Feature centrality and conceptual coherence. Cognitive Science, 22, 189–228] and the generative model [Rehder, B., & Kim, S. (2006). How causal knowledge affects classification: A generative theory of categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 659–683]—and discusses methodological issues such as the testing of natural versus novel (artificial) categories and the interpretation of classification tests. Directions for future research are identified.