Once people know the outcome of an event, they tend to overestimate what could have been anticipated in foresight. Although typically considered to be a robust phenomenon, this hindsight bias is subject to moderating circumstances. In their meta-analysis, Christensen-Szalanski and Willham (1991) observed that the more experience people have with the task under consideration, the smaller the resulting hindsight bias is. In a series of simulations we investigated whether the recently proposed RAFT model (Hoffrage, Hertwig, & Gigerenzer, 2000) can account for this "expertise effect." Indeed, we observed that the more comprehensive people's knowledge is in foresight, the smaller their hindsight bias is (Hertwig, Fanselow, & Hoffrage, in press). In addition, we made two counterintuitive observations: First, the relation between foresight knowledge and hindsight bias appears to be independent of how knowledge is processed. Second, even if foresight knowledge is false, it can reduce hindsight bias. In conclusion, our investigations confirm the utility of developing and testing precise process models of hindsight bias.