Unpredictable and rapidly changing electric sector technologies, policies, and market characteristics require utility planners to develop resource expansion portfolios that are cost-effective against a range of futures. Methods to explicitly address planning under uncertainty and identify resource plans that are either robust or adaptive to a wide variety of futures are emerging but may take some time to become integrated into mainstream planning tools. Leveraging Monte Carlo-based analyses can provide an alternative means of using existing planning models to estimate the robustness of candidate resource portfolios under different futures. This project investigates using a Monte Carlo-style analysis and value at risk theory with EPRI’s Regional Economy, Greenhouse Gas, and Energy Model (REGEN) to efficiently evaluate the potential robustness of two discrete generation capacity expansion planning portfolios for Canada against natural gas price and nuclear VO&M cost uncertainties through 2050. Portfolios are evaluated based on net present costs and overall sensitivity to the uncertainties. Results and observations motivate several future research opportunities.