Generalization of learning can arise from 2 distinct sources: failure to discriminate a novel test stimulus from the trained stimulus and active extrapolation from the trained stimulus to the test stimulus despite them being discriminable. We investigated these 2 processes in a predictive learning task by testing stimulus discriminability (identification of the trained stimulus) as well as generalization of learning (outcome expectancy). Generalization gradients were broader for expectancy than for identification, in both single cue and differential (discrimination) designs, implying a substantial extrapolation component for the most dissimilar stimuli. The shapes of the expectancy gradients were strongly determined by the training design (single cue vs. differential) and by the rules inferred by participants (similarity vs. linear). By contrast, the identification gradients were unaffected by the training design or inferred rules and were equivalent for predictive and nonpredictive stimuli. These results indicate that perceptual discriminability plays a substantial role in generalization, but it is largely unaffected by associative learning. Instead, learning appears to impact on generalization via an independent extrapolation component which involves cognitive processes such as inductive reasoning.