In the entire world, cardiovascular diseases (CVDs) are the main cause of death. According to estimates, 17.9 million deaths worldwide in 2019 were attributable to CVDs, or 32% of all fatalities. Heart attack and stroke deaths accounted for 85% of these fatalities. The majority of CVD fatalities occur in low- and middle-income nations. In 2019, non communicable illnesses caused 17 million premature deaths (before the age of 70), and 38% of those fatalities were attributable to CVDs. By addressing behavioural risk factors like tobacco use, unhealthy eating and obesity, inactivity and problematic alcohol consumption, the majority of cardiovascular illnesses can be avoided. Early detection of cardiovascular disease is crucial in order to start treatment with counseling and medication. This study examines the effectiveness of machine learning algorithms in the diagnosis of cardiovascular diseases.