Seasonal influenza affects a substantial proportion of the human population every year. Due to continued evolution of the influenza virus, a single individual can be repeatedly infected by strains differing in their antigenic makeup. Evolution of the virus population necessitates the updating of the seasonal influenza vaccine. In constructing an influenza vaccine, a particular virus strain must be chosen approximately one year in advance to allow for sufficient quantities of vaccine to be manufactured. The degree of antigenic similarity between this vaccine strain and the population of circulating strains is critically important to public health. Consequently, I propose to adapt the sophisticated methodology of state-of-the-art phylogenetic inference to allow for nuanced predictions of the future evolution of the virus population. Given the genetic sequences of past and current influenza strains, it is my goal to provide an estimate, and an associated degree of confidence, of what strain will predominant in the future. These estimates will draw from multiple characteristics of influenza strains, incorporating patterns of sequence substitution, patterns of population turnover, patterns of geographic movement and patterns of antigenic change. This methodology will be assessed by validating predictions of previous years to historical outcomes. If the resulting methodology is successful in its predictions, then it can be immediately adopted to inform public health decisions. However, if virus evolution is too stochastic, accurate prediction may be an impossibility. Regardless of the accuracy of predictions, the outcomes of this research will have substantial value to the general study of the evolutionary dynamics of virus populations.