Phylogenetic approaches to biogeography are rapidly becoming more sophisticated. Four types of models are being explored in the literature: ( a ) diffusion models, ( b ) island models, ( c ) hierarchical vicariance models (HVMs), and ( d ) reticulate models. Diffusion models are used primarily for phylogeographic inference but can also offer insights into geographic discontinuities of significance on longer time scales. For the island models, statistical approaches are now well developed and typically offer more detailed insight than parsimony analysis. In contrast, parsimony may still be the best option for HVM analysis, because existing statistical approaches do not yet accommodate dispersal. The proposed probabilistic models of reticulate scenarios remain poorly understood, even though they may currently do the best job of integrating diversification processes into biogeographic analysis. Statistical approaches are gaining in popularity across the field, in part because of the flexibility of stochastic modeling. This allows investigators to address important related processes, such as ecological interactions and climate change, in biogeographic inference.