This article shows how statistical matching methods can be used to select "most similar" cases for qualitative analysis. I first offer a methodological justification for research designs based on selecting most similar cases. I then discuss the applicability of existing matching methods to the task of selecting most similar cases and propose adaptations to meet the unique requirements of qualitative analysis. Through several applications, I show that matching methods have advantages over traditional selection in "most similar" case designs: They ensure that most similar cases are in fact most similar; they make scope conditions, assumptions, and measurement explicit; and they make case selection transparent and replicable.