The development of a pay-adjustment procedure for implementing performance-related specifications is a difficult task for most state highway agencies because of such problem areas as selecting pay-factor items, modeling the relationship between stochastic variability of pay-factor items and pavement performance, and determining an overall lot pay adjustment. An effective way to develop a scientific pay-adjustment procedure by incorporating the life-cycle cost analysis-embedded Monte Carlo simulation (LMCS) approach was needed. Presented is an application to a real project to determine a pay adjustment by using the data in the pavement management information systems at the Wisconsin Department of Transportation as an exemplary to other state highway agencies. It was concluded that the proposed LMCS approach can effectively model an overall pay adjustment by considering both the inherent variability in pay-factor items and the interactions among individual pay-adjustment schedules. A sensitivity analysis was conducted to determine the relative importance of pay-factor items and to validate the application of the LMCS approach.