The growing desire for sponsors of power generation projects to share risk with the lenders has promoted the use of computational tools, simulating and evaluating from a techno-economic viewpoint long-term, high-risk projects. Such models need to include reliable engine diagnostics, life cycle costing and risk analysis technique. This work consisted in designing a Decision Support System (DSS) for the assessment of power generation projects using industrial gas turbines in combined cycle. The software, programmed in Visual Basic in Excel in a windows-frame, runs an external application named Pythia, which has been developed by the Department of Propulsion, Power, Energy and Automotive Engineering at Cranfield University. It can perform gas turbine performance simulations, including off-design conditions, with or without degradation effects providing thus reliable engine diagnostics. Steam cycle models including different heat recovery steam generator configurations have been developed to simulate steam turbine design and off-design performance. Plant performance simulation takes into account off-design conditions, part-load governing strategies and degradation effects. Besides a robust economic mode and a life cycle costing model including maintenance-planning assessments offer a wide range of possible operating and economic scenarios. The degree of uncertainty relating to technical and economic factors is assessed using normal distributions, and the level of risk is then evaluated using a risk analysis technique based upon the Monte Carlo method. The DSS provides all sorts of charts and techno-economic figures in order to support the decision making through an effective user-friendly window-oriented interface.