Problem: The practice of scenario plan- ning is often too focused on developing a single preferred scenario and fails to adequately consider multiple uncertain futures. The U.S. Department of Housing and Urban Development recently awarded grants for scenario planning at regional and metropolitan scales that further promote this practice. However, a lack of systematic analysis of uncertainty limits the role of scenario planning. Purpose: The purpose of this article is to demonstrate how to incorporate uncertainty into large-scale scenario analysis and then use that framework to identify contingent and robust plans. Methods: We adapt the concepts of controllable internal options and uncontrol- lable external forces and consider their interactions in order to develop future scenarios and identify contingent and robust decisions. We then apply this technique using advanced econometric, land use, and transportation models developed for the Baltimore–Washington metropolitan region and its vicinity. Finally, based on the results of a hypothetical, yet plausible, exercise, we show how contingent and robust decisions can help local and regional governments develop contingent and robust plans. Results and conclusions: Scenarios developed as a combination of internal options and external forces allow us to identify a wider range of future impacts than in traditional metropolitan scenario planning. Robust plans support choices that offer benefits across scenarios. Contingent plans can be tailored to specific futures. Takeaway for practice: By providing a way to think systematically about uncer- tainty, scenario analysis promises to improve the efficacy of large-scale planning.