Objective: To determine the rate of off-label prescribing of statins for patients diagnosed with hypertension and/or diabetes and to identify the patient and physician characteristics affecting the prescribing of statins. Methods: Data from the National Ambulatory Medical Care Survey (NAMCS) for the year 2005 was used. Hypertension and diabetes visits were identified based on the ICD-9-CM diagnoses code, reason-for-visit codes, and an affirmative answer to a question asking whether the patient is currently suffering from hypertension/diabetes. Statin visits were identified using the NAMCS generic drug codes. “On-label” statin visits defined as visits having ICD-9-CM diagnoses code, reason-for-visit code for hyperlipidemia, Acute Myocardial Infarction, Ischemic Heart Disease, Angina, & Atherosclerosis, a CPT-4 code for revascularization, or a lipid lab test were excluded. Multivariate logistic regression models were applied using Stata 9 to take into account the complex survey design. Results: In 2005, 23.1 million diabetes visits (95% CI=18.3-28.0 million), and 50.1 million hypertension visits (95% CI=40.7-59.5 million), resulted in a statin prescription representing 24%, and 22%, of the total visits for the two conditions respectively. Patients aged 41-60 years (OR=3.49, 95% CI=1.43-8.47) or 61-80 years (OR=3.98, 95% CI=1.40-11.31), or those from metropolitan areas (OR: 2.23, 95% CI: 1.11-4.48) were more likely to receive a statin prescription compared to the respective baseline groups. Whereas residing in the northeast (OR=0.44, 95% CI=0.26-0.75) or midwest (OR=0.40, 95% CI=0.21-0.77) regions or being black (OR=0.50, 95% CI=0.29-0.87) predict significantly lower odds of receiving statin prescription compared with the south region and nonhispanic whites or other race groups. Conclusion: As expected, age was the most important factor determining the prescribing of statins in hypertension and/or diabetes. It is not clear if these rates of statin prescribing reflect aggressive off-label prescribing or undercoding of on-label diagnoses. Data on more years needs to be analyzed to confirm the findings.