In this study, we apply an agent-based modeling approach to understand individual visitors’ multidestination travel patterns and the spatial spillover effects in visitor flows as an aggregate outcome. Based on previous literature, we specify three hypothetic visitor categories (global optimizers, sequential optimizers, and radial optimizers) according to visitors’ attraction selection rules. We conduct an ABM simulation with a sample of 341 Chinese cities as destinations and 1,990 attractions to measure the degree of spillover between destinations by observing the frequency with which visitors traveling across destination boundaries visited attractions in other destinations. The simulation results demonstrate slightly different spillover effects based on visitor type and highlight three regions with particularly strong spillover effects: the Bohai Rim region, the Yangtze River Delta region, and the Sichuan and Chongqing region. These results appear consistent with those of exploratory spatial data analysis in a validation check. Lastly, policy implications are provided.