Introduction: Asymptomatic carotid artery stenosis is one of the factors that causes stroke. Other factors such as high blood pressure, cardiac diseases, smoking, diabetes, and physical inactivity may also cause the disease. Understanding and identifying the factors that cause carotid artery stenosis will help in prevention of acute stroke. Using data mining techniques, this study was aimed to discover the rules and relations that are effective in identifying asymptomatic carotid artery stenosis. Materials and Methods: To find the best approach, logistic regression (LR), genetic algorithm (GA), and chi-square test were used to predict carotid artery stenosis in patients. Results: 372 participants, 173 women (% 46.5) and 199 men (% 53.5), with an average age of 70.74± 5.29 were investigated. The results showed gender, smoking, coronary artery disease, high blood pressure, inactivity, prevention of pregnancy by medication, uremia (excessive amounts of urea and other nitrogenous compounds in the blood), and pulse rate environment are the significant risk factors for asymptomatic carotid artery. In addition, GA was a better method for this approach compared to LR. Conclusion: Our study revealed that coronary artery disease and hypertension are important factors in predicting and prognosis of asymptomatic carotid artery stenosis.