The purpose of this project is to determine which Starbucks drinks among all coffee and tea options are best for cardiovascular disease (CVD) prevention. A health index was constructed considering different variables, including: saturated fat, cholesterol, sodium, carbohydrates, dietary fiber, sugars, protein, and caffeine. Each variable was assigned a weighting coefficient, with lower coefficients assigned to the factors that are more harmful and higher ones to those that are more beneficial. Therefore, drinks with the highest health index are determined to be the most beneficial to preventing CVD. Principal Components Analysis (PCA) was used to explore all factors in the analysis and to inform on the utility of the health index in relation to its link to CVD prevention. In this paper, Principle Component 1 is more relevant to unhealthy components such as sugars, carbohydrates, saturated fat, and total fat. Thus, each of these variables were assigned negative weight coefficients in the Health Index. Additionally, Dietary Fiber and Caffeine are most opposite against the other components along the x-axis of the Principle Component.