Budget constraints and competing opportunities demand thoughtful evaluation of projects before investment. Significant uncertainty surrounds travel choices, demographic futures, project costs, and model parameters. The impact of this uncertainty was explored with the use of hundreds of sensitivity test runs conducted across 28 random parameter sets to evaluate highway capacity expansion and toll project scenarios in Austin, Texas. The effects of different parameter sets on project benefit–cost ratios, crash counts, emissions, traffic volumes, and tolling revenues were examined in detail. Linear regression results showed that link capacity, link performance parameters, and their covariation were key to the results, followed by the elasticity of demand, trip growth rates, and values of travel time.