All industrial power systems are influenced by ambient parameters, and power plant output fluctuates significantly with changes in ambient conditions such as pressure, temperature, and humidity. The use of an inlet conditioning system is frequently proposed to lower the temperatures at the inlet of an industrial gas turbine engine, particularly in hot and arid regions. To evaluate such a system, a robust design methodology has been developed whereby ambient operating conditions and their impacts can be modeled easily and accurately. Ambient models are developed that are specific to a given locale and consider daily and annual variations in temperature and humidity. A robust design is one that has a high probability of meeting design goals, and at the same time, is insensitive to operational uncertainty. This paper addresses the possibility of enhancing the robustness of gas turbine engines by means of technology additions. The results of this study have been developed in part using the probabilistic analysis techniques developed at the Aerospace System Design Laboratory at Georgia Tech, and they demonstrate how differing ambient conditions can affect the decision to install an inlet conditioning system with the engine [1]. An industrial gas turbine power plant is modeled, and the ambient models are integrated with the engine model and used to predict the overall impact on power plant net revenue over a year-long period of operation. This is done at four specified locales each with widely different ambient characteristics.