The current pricing climate for natural gas and liquid transportation fuels adds a significant amount of uncertainty when designing new natural gas to liquid transportation fuel (GTL) refineries. Robust optimization is a useful tool for optimization under uncertainty and can be specifically applied to the problem of GTL process synthesis under feedstock price, product price, and investment cost uncertainty. Using historical data to define uncertain price parameters according to an assumed uniform distribution, a process synthesis superstructure with an uncertain objective function was created to maximize the profit of a GTL refinery. Recently developed, tight probabilistic bounds were used a priori and a posteriori in an iterative method to provide solutions with known probabilities of constraint violation for three different uncertainty sets. The relative impact of price and investment cost uncertainties are discussed, as is the impact of uncertainty on the overall guaranteed profit of a refinery, the refinery topology, and product distributions. The profitability results with probabilistic guarantees provide useful information for potential GTL refinery investors in the current uncertain energy markets.