Background: In recent years, hemoglobin A1c (HbA1c) is accepted among the algorithms used for making diagnosis for diabetes and prediabetes since it does not require subjects to be prepared for giving a blood sample. The aim of this study is to assess the performance of HbA1c against fasting plasma glucose (FPG) and oral glucose tolerance test (OGTT) in detecting prediabetes and diabetes. Materials and Methods: A total of 315 subjects were included in this study. The success of HbA1c in distinguishing the three diagnostic classes was examined by three-way receiver operating characteristic (ROC) analysis. The best cut-off points for HbA1c were found for discriminating the three disease status. Results: The performance of HbA1c, measured by the volume under the ROC surface (VUS), is found to be statistically significant (VUS = 0.535, P < 0.001). The best cut-off points for discriminating between normal and prediabetes groups and between prediabetes and diabetes groups are c1 = 5.2% and c2 = 6.4% respectively. Conclusion: The performance of HbA1c in distinguishing between the prediabetes and diabetes groups was higher than its ability in distinguishing between healthy and prediabetes groups. This study provides enough information to understand what proportion of diabetes patients were skipped with the HbA1c especially when the test result is healthy or prediabetes. If a subject was diagnosed as healthy or prediabetes by HbA1c, it would be beneficial to verify the status of that subject by the gold standard test (OGTT and FPG).