Familial hypercholesterolemia (FH) is a genetic disorder that causes high concentration of bad cholesterol from birth. While genetic testing is the norm, it is expensive and not always available. We aim to create machine learning algorithms that predict the outcome of a genetic test based on a blood sample and patient's characteristics. We will then assess whether our algorithms have higher predictive powers than clinical scoring systems.