Whether forced by economic conditions or internal motivations, contractors may choose to minimize their mark-up margins in order to maximize their chances of winning a bid. Such bidding conditions render contractors sensitive towards all types of risks associated with executing a project. This research aims at providing contractors with a framework through which they can reduce their bid prices to be able to compete in low biding conditions. This aim is realized through identifying risk elements that have the greatest impact on projects’ costs in the Egyptian construction industry. Work on this research follows a risk path approach consisting of risk sources, risk events, and risk consequences, and vulnerability factors consisting of robustness factors, resistance factors and sensitivity factors, whose relationships and risk paths are mapped through an ontology model. The weights characterizing that relationship between each of these elements is estimated through a three-phase model that utilizes both optimization and Artificial Neural Networks (ANN), through 52 risks cenarios collected from 35 experts in the Egyptian Construction industry. Outputs generated by the model comprise of five sets of weights. Each set represents the effect of one risk path element on a subsequent element, collectively demonstrating the relations connecting the risk path elements to cost overruns. The model’s outputs showed that that 35 percent of the top 20 Robustness factors are related to project design. Lack of contractor’s technical resources rank higher than that of contractor’s financial resources in terms of their effect on Risk events. Project type has the most impact on project cost overrun, followed by Project delivery method. Further, delays due to bureaucracy whether from the owner or the government’s side rank at the bottom of the list
