This paper proposes a Machine Learning or ML-based strategy to accurately identify a possible heart disease patient. Unlike traditional diagnostic systems which are time-consuming and have human error involved to take care of the patient and diagnose the patients. The proposed system identifies whether the patient will face these kinds of diseases in near future or not. The system is developed based on machine learning techniques such as Naive Bayes, XGBoost gradient classifier, support vector machine, and decision tree. Some external factors were also considered which may lead to heart disease in the future. Furthermore, an integrated web application has been developed that alert and gives a user-friendly interface for recognition and prediction. Thirteen diagnostic factors and five environmental factors are analyzed. The proposed diagnosis system attained good precision as compared to previous methods recommended earlier. In addition, the system can easily be implemented in the public domain to spread awareness regarding heart disease, and it also talks about the possibility of heart disease in near future.Povzetek: Predstavljeni sistem zazna morebitno srčno bolezen iz trinajstih diagnostičnih in petih okoljskih dejavnikov z uporabo algoritmov strojnega učenja.

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