The life cycle cost and environmental impacts of electric vehicles are very uncertain, but extremely important for making policy decisions. This study presents a new model, called the Electric Vehicles Regional Optimizer, to model this uncertainty and predict the optimal combination of drivetrains in different U.S. regions for the year 2030. First, the life cycle cost and life cycle environmental emissions of internal combustion engine vehicles, gasoline hybrid electric vehicles, and three different Electric Vehicle types (gasoline plug-in hybrid electric vehicles, gasoline extended range electric vehicle, and all-electric vehicle) are evaluated considering their inherent uncertainties. Then, the environmental damage costs and the water footprint of the studied drivetrains are estimated. Additionally, using an Exploratory Modeling and Analysis method, the uncertainties in the life cycle cost, environmental damage cost, and water footprint of studied vehicle types are modeled for different U.S. electricity grid regions. Finally, an optimization model is coupled with Exploratory Modeling and Analysis to find the ideal combination of different vehicle types in each U.S. region for the year 2030. The findings of this research will help policy makers and transportation planners to prepare our nation's transportation system for the influx of electric vehicles. •An electric vehicle regional optimization model is created to address uncertainty.•Life cycle cost, environmental cost, and water footprint range of vehicles are modeled.•Internal combustion vehicles have lowest cost, highest environmental impact.•Electric vehicles have relatively low cost and lowest environmental impact.•The optimal U.S. fleet mix in 2030 will consist of electric and gasoline vehicles.