A probabilistic model and software tool has been developed to assist in the selection, design, and monitoring of long-term covers for contaminated subsurface sites. The software platform contains multiple modules that can be used to simulate relevant features, events, and processes that include water flux through the cover, source-term release, vadose-zone transport, saturated-zone transport, gas transport, and exposure pathways. The component models are integrated into a probabilistic total-system performance-assessment model within a drag-and-drop software platform. Uncertainty and sensitivity analyses can be conducted that yield the following primary benefits: (1) quantification of uncertainty in the simulated performance metrics; (2) identification of parameters most important to performance; and (3) comparison of alternative designs to optimize cost and performance. A case study has been performed using the Monticello Mill Tailings Site in Utah to illustrate the important features and benefits of the modeling approach and software.