Transportation projects are high-cost investments. For this reason in order to perform correct decision making process special approaches and methods have to be used in feasibility analysis. Benefit Cost Analysis (BCA) is a widely used method all over the world and in Turkey for the economical evaluation of the transportation projects. But, the most important disadvantage of this method is the difficulties in predicting the costs, missing and lacking data and the uncertainty in the long-term analysis period risks affecting the results negatively. In order to avoid this risk, protective measures such as sensitivity analysis and probability distributions are used in the traditional benefit – cost analysis. But, in a project where there are high uncertainties and approximate data are present the said methods are becoming insufficient in real-life applications. Especially, the countries with a quickly changing socio-economic structure, for the transportation projects having long-term analysis period there are uncertainties in predicting parameters such as traffic volumes, accident data, time value etc. As a result of all those items the evaluation of the feasibility of the transportation projects is always facing risks of wrong decision-making. Therefore, the need to develop a more sophisticated method eliminating all the uncertainties of the traditional benefit cost analysis becomes evident. This paper, aims to develop a model that will contribute to the traditionally widely used benefit cost analysis in economical evaluation of transport projects by the Turkish State Highway Authority. Through this proposed model it is also aimed to eliminate the missing and uncertain data and wrong estimations in feasibility analyses. As a result the paper is proposing an intelligent system framework, utilising The Fuzzy Cognitive Map for the transportation projects’ benefit cost analysis