This paper examines the key determinants of U.S. Gross Domestic Product (GDP) growth using a combination of Keynesian economic theory and statistical modeling. By leveraging ideal keynesian variables along with statistical algorithms (i.e. Lasso-Ridge regression), this study aims to provide a better understanding of the factors influencing GDP growth. In particular, we focus on variables such as consumption, investment, government spending, and net exports, central to Keynesian economic theory, while incorporating more modern variables like population, housing price index, and corporate profits.