Migration, the seasonal movement of individuals among different locations, is a behavior found throughout the animal kingdom. Although migration is widely studied at taxonomically restricted levels, cross-taxonomic syntheses of migration are less common. As a result, we lack answers to broad questions such as what ultimate factors generally drive animal migration. Here we present such a synthesis by using a spatially explicit, individual-based model in which we evolve behavior rules via simulations under a wide range of ecological conditions to answer two questions. First, under what types of ecological conditions can an individual maximize its fitness by migrating (vs. being a resident)? Second, what types of information do individuals use to guide their movement? We show that migration is selected for when resource distributions are dominated more by seasonality than by local patchiness, and residency (nonmigratory behavior) is selected for when the reverse is true. When selected for, migration evolves as both a movement behavior and an information usage strategy. We also find that different types of migration can evolve, depending on the ecological conditions and availability of information. Finally, we present empirical support for our main results, drawn from migration patterns exhibited by a variety of taxonomic groups.