Despite the identification of crash hotspots as a first step of the roads safety management process, with various effective black spots identification (HSID) methods, only a few researchers have compared the performance of these methods; also it is not clear which test is the most consistent in the black-spots identification. In this research, seven commonly applied HSID methods (accident frequency (AF), PIARC coefficient based equivalent property damage only (EPDO), P-value (Islamic Republic of Iran Ministry Roads and Urban development), accident rate (AR), combined criteria, empirical Bayes (EB), societal risk-based) were compared against six robust and informative quantitative evaluation criteria (site consistency test, method consistency test, total rank differences test, total score test, sensitivity test and specificity test). These tests evaluate each method performance in a variety of areas, such as efficiency in identifying sites that show consistently poor safety performance, reliability in identifying the same black spots in subsequent time periods .To evaluate the HSID methods, three years of crash data from the Kerman state were used. Analytical Hierarchy Process (AHP) method has been used for determination the importance coefficients of evaluation tests and as a result, showed that the total rank differences test is the most appropriate test. The quantitative evaluation tests showed that the EB method performs better than the other HSID method. Test results highlight that the EB method is the most consistent and reliable method for identifying priority investigation locations. Overall, this result is consistent with the results of previous studies. The societal risk-based method performed worst in the all of the tests. It should be noted that advantages associated with the EB method were based on crash data from one of the road in Iran country, so the relative performances of HSID methods may change when using other crash data. However, the study results are consistent with earlier findings.