The inference of an accurate phylogeny relating the species of the order Primate is a central focus of the field of evolutionary primatology. Most previous studies of primate phylogeny have used DNA sequence data from individual loci or multiple genes in concatenation (i.e., a super gene) to produce gene trees that are assumed to represent species relationships. For example, while early studies used _-globin gene sequence data, recent studies have expanded the number of loci used by merging them into a single, larger locus which may be analyzed as a single gene. This so-called super-matrix approach is commonly used to infer phylogenies at high taxonomic levels (i.e., families, orders, and classes), including the order Primate. However, this method assumes complete linkage between loci and fails to account for incomplete lineage sorting, which is a product of divergence times and population size and results in gene trees that are inconsistent with species relationships. In this study, we analyze a previously published dataset consisting of 54 partial gene sequences from 191 primate species using a multi-locus coalescent species tree model implemented in the BEAST software package to infer the evolutionary history of primates. Notably, this analysis will also produce estimates of ancestral primate population sizes (Ne) and more accurate divergence date estimates by taking advantage of the independent information encoded in each partial gene sequence. Importantly, our multi-locus species phylogeny and ancestral population size estimates allow us to test prevailing theories about the tempo and mode of primate evolution and divergence.