There are unique cases when designing products where a prototype is required to demonstrate critical operations of a system or subsystem such that it will serve as a basis for how the design will move forward. These prototypes are oftentimes on the critical design path. Due to the fact there is typically some aspect of a prototype that is not well understood there can be a considerable amount of uncertainty associated with the amount of resources needed to design such a prototype. The goal of this thesis is to address how to systematically reduce uncertainty for the purpose of creating a robust cost estimate. This statement does highlight the problem of defining what a robust estimate is, which results in addressing the key question driving this research: "When is enough information gathered to generate a robust estimate for the design of prototype systems?" The crux of the problem lies in how to characterize the interactions and uncertainty associated with cost, schedule, and performance. Additionally, the breakdown of a prototype system into its subsystems results in errors exist at each division. The result is a cost estimation method that has been generated by leveraging the principles of design methodology. Two test cases are applied including one theoretical model, and one project from the Georgia Tech Research Institute (GTRI). The GTRI project was work performed for the Georgia Department of Transportation related to the filling of cracks on asphalt road surfaces. These examples are evaluated from the view point of the Validation Square in order to verify the effectiveness beyond example problems.