Atherosclerosis, and its most common manifestation, coronary artery disease (CAD), are rather common causes of morbidity and mortality worldwide. Recognition of its various risk factors is important to planning effective preventive measures. After the homocysteine theory was presented in 1969, attention has been directed toward the serum homocysteine level as a coronary artery disease risk factor. The authors aimed to assess the relationship between hyperhomocysteinemia and CAD in an Iranian population. In a case control study, 197 individuals (male: 123 [62.4%]) who were scheduled for coronary angiography were selected. Venous samples were taken from the patients in fasting state before angiography. Data about age, sex, risk factors (eg, hypertension, diabetes, smoking, hyperlipidemia, obesity) were obtained from prepared questionnaires. Homocysteine levels in patients were measured by ELISA method. A homocysteine level above 15 mumol/liter was considered high. Angiography reports and homocysteine levels were analyzed by independent sample t test, one-way ANOVA, multiple linear regression, and stratified analysis. In comparison with the patients with normal angiography reports (32.5%), patients with abnormal angiography reports (67.5%) had increased levels of homocysteine (p = 0.001). About 28.1% of patients with normal angiography reports had hyperhomocysteinemia. After further evaluation, linear correlations were detected between the numbers of involved vessels and homocysteine level (p = 0.000). Multiple linear regression analysis of data detected that in individuals without any risk factors, the relationship was stronger and more meaningful (p = 0.000). These data show that hyperhomocysteinemia is related to CAD as an independent risk factor. In individuals without any risk factors a linear correlation between homocysteine level and numbers of coronary artery involvement was present. If this equation is confirmed prospectively in other studies, the level of plasma homocysteine may he used as a noninvasive way of predicting the number of diseased coronary arteries.