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The aim of the present study is the representation of a method to identify and prioritize accident-prone sections (APSs) based upon efficiency concept to emphasize accidents with regard to traffic, geometric and environmental circumstances of road which can consider the interaction of accidents as well as their casual factors. This study incorporates the segmentation procedure into data envelopment analysis (DEA) technique which has no requirement of distribution function and special assumptions, unlike the regression models. A case study has been done on 144.4km length of Iran roads to describe the approach. Eleven accident-prone sections were identified among 154 sections obtained from the segmentation process and their prioritization was made based on the inefficiency values coming from DEA method. The comparisons demonstrated that the frequency and severity of accidents would not be only considered as the main factors for black-spots identification but proper rating can be possible by obtaining inefficiency values from this method for the road sections. This approach could applicably offer decision-making units for identifying accident-prone sections and their prioritizations. Also, it can be used to prioritize intersections, roundabouts or the total roads of the safety organization domain.