We assess the performance of three hospital merger simulation methods by means of a Monte Carlo experiment. We ﬁrst specify a rich theoretical model of hospital markets and use it to generate “true” price eﬀects of a large number of hospital mergers. We then use the theoretical model to generate the data that would be available in a real-world prospective merger analysis and apply the merger simulation methods to those data. Finally, we compare the predictions of the merger simulation methods to the true price eﬀects. While there is some heterogeneity in performance, all three simulation methods perform reasonably well.