Accuracy of phylogenetic methods may be assessed in terms of consistency, efficiency, and robustness. Four principal methods have been used for assessing phylogenetic accuracy: simulation, known phylogenies, statistical analyses, and congruence studies. Simulation studies are useful for studying accuracy of methods under idealized conditions and can be used to make general predictions about the behavior of methods if the limitations of the models are taken into account. Studies of known phylogenies can be used to test predictions from simulation studies, thus providing a check on the robustness of the models (and possibly suggesting refinements for future simulations). Statistical analyses allow general predictions to be applied to specific results, facilitate assessments as to whether or not sufficient data have been collected to formulate a robust conclusion, and indicate whether a given data set is any more structured than random noise. Finally, congruence studies of multiple data sets can be used to assess the degree to which independent results agree and thus the minimum proportion of the findings that can be attributed to an underlying phylogeny. These different methods of assessing phylogenetic accuracy are largely complementary, and the results are consistent in identifying a large class of problems that are amenable to phylogenetic reconstruction.