1 INTRODUCTIONThe heart is the fundamental part of the body. Heart failure is a serious medical situation in which this master organ does not function properly. Dysfunction of the heart can impact all organs of the body since it is affiliated with all parts of the body through its arteries and veins. One of the most dangerous and insidious heart diseases is heart attack. It can be defined as chest pain associated with constriction of the coronary vessels, called atherosclerosis. The two main indicators of heart attack that this work has focused on are the type of chest pain and the rate of coronary vessel obstruction. The Centers for Disease Control and Protection (CDC) has estimated that approximately 715,000 Americans suffer a heart attack each year. . 525,000 of these are first-time heart attacks and 190,000 occur in people who have already had a heart attack [1]. Because of these dangerous consequences, there should be a way to predict a heart attack. Heart diseases can be diagnosed by their signs and symptoms. Heart attack is one of the riskiest heart conditions and has the same signs and symptoms in addition to the buildup of plaques in the coronary arteries that rupture inside the arteries and unstable angina that can be an impending sign of a heart attack. is the automatic study (analysis) of stored data to obtain results and find patterns beyond that data. Nowadays, there are various diagnostic devices and patient medical records that can store a huge amount of data [2]. Therefore, such medical data that may indicate a heart attack must be stored and processed using a neural network based on a data mining technique; to create a decision-making system for heart attack prediction. The overall stage...... middle of document...... 1-8.[4] Miss Chaitrali S. Dangare, Dr. Mrs. Sulabha S. Apte,2012. “A Data Mining Approach for Heart Disease Prediction Using Neural Networks”, International Journal of Computer Engineering and Technology (IJCET), Vol. 3, number 3, pp. 30-40.[5] Dilip Roy Chowdhury, Mridula Chatterjee RK Samanta, 2011. "An artificial neural network model for diagnosis of neonatal diseases", International Journal of Artificial Intelligence and Expert Systems (IJAE), vol. 2, number 3, pp. 96-106.[6] https://www.physics.harvard.edu/uploads/files/thesesPDF/Fiete.pdf[7] K. Anil Jain, Jianchang Mao, and K. M. Mohiuddi, 1996. “Artificial Neural Networks: A Tutorial,” IEEE Computers, pp. .31-44.[8] R. Rojas, (1996) “Neural networks: a systematic introduction”, Springer-Verlag.[9] Cleveland Database: http://archive.ics.uci.edu/ml/datasets/Heart+Disease