Pavement thickness design traditionally has been based on empiricism. However, mechanistic-empirical (M-E) design procedures are becoming more prevalent, and there is a current effort by AASHTO to establish a nationwide M-E standard design practice. Concurrently, an M-E design procedure for flexible pavements tailored to conditions within Minnesota has been developed and is being implemented. Regardless of the design procedure type, inherent variability associated with the design input parameters will produce variable pavement performance predictions. Consequently, for a complete design procedure, the input variability must be addressed. To account for input variability, reliability analysis was incorporated into the M-E design procedure for Minnesota. Monte Carlo simulation was chosen for reliability analysis and was incorporated into the computer pavement design tool, ROADENT. A sensitivity analysis was conducted by using ROADENT in conjunction with data collected from the Minnesota Road Research Project and the literature. The analysis demonstrated the interactions between the input parameters and showed that traffic weight variability exerts the largest influence on predicted performance variability. The sensitivity analysis also established a minimum number of Monte Carlo cycles for design (5,000) and characterized the predicted pavement performance distribution by an extreme value Type I function. Finally, design comparisons made between ROADENT, the 1993 AASHTO pavement design guide, and the existing Minnesota design methods showed that ROADENT produced comparable designs for rutting performance but was somewhat conservative for fatigue cracking.