Hypertension (HTN) is the third leading cause of morbidity and mortality worldwide. It represents the single greatest preventable cause of death in humans and one of the most important modifiable risk factor for cardiovascular diseases. Financial and public health consequences of both hypertension and the failure to control it are enormous. Identification of different risk factors is important for the prevention and control of hypertension. This paper examines the most important risk factors of hypertension among age, cigarette smoking, stress, alcoholism, sedentary life style, family history, comorbidity, arteriosclerosis using discriminant analysis, logistic regression and neural networks. It reveals that, among age, cigarette smoking, stress, alcoholism, sedentary life style, family history, comorbidity, arteriosclerosis; age and family history are the most important predictors. Moreover, based on neural networks analysis, the model identified not only age and family history but also stress, alcoholism and comorbidity as important predictors also.