This thesis seeks to predict the results of the presidential election in the United States, with a specific interest in swing states. I construct a methodology to predict the difference between the state and national two-party vote share for all 50 states plus D.C. using economic variables such as the change in the unemployment rate, the growth of real per capita Gross Domestic Product, Gallup poll ratings, and the ideology of the candidate. The methodology presented also allows the number of swing states to adjust between election years by giving each state its own coefficient on the difference between the state and national change in the unemployment rate. The resulting State-National Gap Model is then used to predict the two-party vote share for the Democrats using regression analysis with panel data for the elections from 1992-2008. My model is tested against the 2012 election and successfully predicts 49 out of 50 states as well as D.C.