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 segmentation procedure into data envelopment analysis (DEA) technique which has no requirement of distribution function and especial assumptions unlike the regression models. A case study has been done in 144.4 km long of Iran\'s roads to describe the approach. Eleven Accidents prone sections were identified among 154 sections obtained from the segmentation process and their prioritization were made based on inefficiency values coming from DEA method. The comparisons demonstrated that the frequency and severity of accidents would not be only con sidered as the main factors for blackspots identification but proper rating can be possible with obtaining inefficiency values from this method for 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 a safety organization domain.

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