Accurate judgments and decisions are crucial for success in many areas of human life. The accuracy of a judgment or decision depends largely on the cognitive process applied. In research on judgment, decision making, and categorization, two kinds of cognitive processes have often been contrasted: exemplar-based processes, which use similarity to previously encountered items to make judgments, decisions, and categorizations, and rule-based processes, which use abstracted cue knowledge. Although most cognitive models of judgment and decision processes assume that people rely on both processes, they differ in whether they assume that one process is selected or that both processes are blended into a single response. The present research takes a functional perspective and investigates what kind of interaction between the two processes leads to accurate responses. Based on cross- validated simulations in real-world domains, it shows that blending rule- and exemplar-based processes generally leads to better judgments than does choosing between them, suggesting that the default strategy should be a blend of both processes, which is abandoned only when feedback justifies it.