Heart disease is a common cause of death worldwide, but diagnosing it early can be challenging. To improve efficiency and reduce costs in the medical field, a system was designed using machine learning algorithms to predict heart disease risks. By analyzing data patterns, the system accurately predicts heart disease using parameters from a large dataset. The Naive Bayes Classifier, Gaussian Naïve Bayes Classifier, and Decision tree algorithms were used to analyze and predict heart diseases effectively.