In modern days, there may be a concerning lack of know-how regarding coronary illness, resulting in preventable deaths. However, there’s a wish on the horizon for modern-day IoT devices to transform healthcare. These devices are ready with superior sensors geared towards early analysis of fitness problems, presenting well-timed signals to both healthcare carriers and patients. These sophisticated gadgets operate inside an IoT framework, facilitating real-time information connection to cloud-based gadget-mastering fashions. In our look, we utilized six classifiers, consisting of Logistic Regression, Naive Bayes, Decision Tree, Random Forest, RandomizedSearchCV, and GridSearchCV, to determine the probability of individuals developing coronary heart ailment or being affected by a coronary heart attack. Among these classifiers, Random Forest established outstanding accuracy in predicting coronary heart sickness, achieving an accuracy price of 90.16%. On the other hand, the GridSearchCV classifier proved to be exceedingly effective in predicting heart attacks, with an accuracy price of 88.2%. This convergence of IoT generation, cloud evaluation, and alerting mechanisms represents an enormous step forward in healthcare. It empowers individuals to take proactive measures regarding their health by leveraging information-pushed insights.