In this article, the authors present and test a formal model that holds that people use information about category boundaries in estimating inexactly represented stimuli. Boundaries restrict stimuli that are category members to fall within a particular range. This model posits that people increase the average accuracy of stimulus estimates by integrating fine-grain values with boundary information, eliminating extreme responses. The authors present 4 experiments in which people estimated sizes of squares from 2 adjacent or partially overlapping stimulus sets. When stimuli from the 2 sets were paired in presentation, people formed relative size categories, truncating their estimates at the boundaries of these categories. Truncation at the boundary of separation between the categories led to exaggeration of differences between stimuli that cross categories. Yet truncated values are shown to be more accurate on average than unadjusted values.