Coronary illness finding has turned into a troublesome assignment in the field of medication. This analysis relies upon an intensive and precise investigation of the patient's clinical tests information on the wellbeing history of a person. The colossal improvement in the field of AI target creating astute mechanized frameworks which helps the clinical specialists in foreseeing as well as settling on choices regarding the sickness. Such a mechanized framework for clinical conclusion would improve convenient clinical consideration followed by appropriate ensuing treatment along these lines bringing about critical life saving. Joining the strategies of characterization in these astute frameworks accomplish at exact determination. Neural Networks has arisen as a significant technique for grouping. Multi-facet Perceptron Neural Network with Back-proliferation has been utilized as the preparation calculation in this work. This paper proposes an indicative framework for anticipating coronary illness. For analysis of coronary illness 14 huge characteristics are utilized in proposed framework according to the clinical writing. The outcomes arranged clearly demonstrate that the planned indicative framework is equipped for foreseeing the gamble level of coronary illness successfully when contrasted with different methodologies.

Keywords : Neural Network; Perception; Back-Propagation