cardiovascular diseases are the leading cause of death around the world. These illnesses related to the malfunction of the heart or blood vessels. The aim of this research work is to establish a fuzzy expert system (FES) for heart diseases diagnosis. This FES design based on cardiovascular risk factors and the major clinical diagnosis parameters using fuzzy logic approach. In this cardiovascular system, we proposed a decision tree based solution for the higher number of rules in order to increase the degree of efficiency. The patient's clinical data extracted from the risk factor of the atherosclerosis disease. This disease is one of specific type of coronary artery disease (CAD) that supported by Cleveland Heart Disease Database (CHDD). The medical system are tested and validated with the data from CHDD and the results show efficiency and accuracy of the developed approach.