This paper develops a comprehensive framework to address uncertainty about the correct factor model. Asset pricing inferences draw on a composite model that integrates over competing factor models weighted by posterior probabilities. Evidence shows that unconditional models record near‐zero probabilities, while postearnings announcement drift, quality‐minus‐junk, and intermediary capital are potent factors in conditional asset pricing. Out‐of‐sample, the integrated model performs well, tilting away from subsequently underperforming factors. Model uncertainty makes equities appear considerably riskier, while model disagreement about expected returns spikes during crash episodes. Disagreement spans all return components involving mispricing, factor loadings, and risk premia.