During the last decade, the concept of composite performance index, brought from economic and business statistics, has become a popular practice in the field of road safety, namely for the identification and classification of worst performing areas or time slots also known as hotspots. The overall quality of a composite index depends upon the complexity of phenomena of interest as well as the relevance of the methodological approach used to aggregate the various indicators into a single composite index. However, current aggregation methods used to estimate the composite road safety performance index suffer from various deficiencies at both the theoretical and operational level; these include the correlation and compensability between indicators, the weighting of the indicators as well as their high “degree of freedom” which enables one to readily manipulate them to produce desired outcomes (Munda and Nardo, 2003, 2005, 2009). The objective of this study is to contribute to the ongoing research effort on the estimation of road safety composite index for hotspots’ identification and ranking. The aggregation method for constructing the composite road safety performance index introduced in this paper, strives to minimize the aforementioned deficiencies of the current approaches. Furthermore, this new method can be viewed as an intelligent decision support system for road safety performance evaluation, in order to prioritize interventions for road safety improvement.