As was known, one of the body’s most important organs is the heart. The heart aids in the purification and circulation of blood to all regions of the body. Many deaths worldwide are caused by heart diseases or cardiovascular diseases. Certain symptoms, like chest pain, an accelerated heartbeat, and difficulty breathing, are regularly noted and assessed. Diagnosing and treating cardiovascular disease are essential medical tasks that help cardiologists treat patients appropriately by ensuring accurate classification. Due to their ability to identify patterns in data, machine learning applications in the medical field have become more and more popular. Numerous approaches and algorithm-based models available, with the goal of detecting heart disease as much as earlier and lowering mortality rates. The performance of various models based on such algorithms and methodologies is surveyed in this chapter. Researchers tend to favor models built using supervised learning algorithms, ML, and DM techniques.