This project performs a data-driven analysis of global life expectancy using R, combining exploratory data analysis, correlation analysis, and regression modeling. Key determinants such as schooling, GDP, and disease prevalence are identified, and a multiple linear regression model is developed to quantify their impact. The model achieves strong explanatory power (R² ≈ 0.77) and reliable predictive performance (RMSE ≈ 4.49), demonstrating the influence of socioeconomic and healthcare factors on life expectancy.