Many people like eating chocolate, but may have some concerns on health risk, especially to people with Cardiovascular or Neurovascular diseases. The objectives of this paper are to use Multivariate Statistics to define a health biometric on choosing a healthy chocolate to patients with heart disease. Chocolate, made from cocoa beans, contains flavonoids which contain antioxidants. Flavonoids are the most abundant polyphenols in human diet. Polyphenols have antioxidant properties which can prevent aging and is also beneficial to heart disease and diabetes patients. People with heart diseases should eat less of saturated fat, trans fat, sodium, and cholesterol. They should eat more dietary fiber. Cocoa flavanols promote healthy blood flow circulation from head to toe. The heart, brain, and muscle depend on a healthy circulatory system. Data has been collected on 20+ chocolate ingredient contents from 60+ different types of chocolate. Multivariate correlation study has found that (1) strong negative correlation between Cocoa and Sugar, and (2) strong positive correlation between Diet Fiber and Iron. Most dark chocolate contains more cocoa, and less sugar. Dietary fiber and iron are high in correlation because of the high cocoa percent. The above two correlations can be further explained by conducting the Hierarchical Clustering Analysis on separating the Dark Chocolate, Milk Chocolate and White Chocolate. The Cocoa and Calcium are the deciding factors to separate these three Chocolates. Based on Chocolate Science. These healthiest chocolate can actually help prevent heart disease. The same approach can be applied to help people with other diseases (cancer, diabetes...).  In Big Data World, the Multivariate Statistics can help connect different data and explain the Science in a predictive or/and empirical modeling.