We present a general framework for probabilistic risk assessment (PRA) of subsurface contamination. PRA provides a natural venue for the rigorous quantification of structural (model) and parametric uncertainties inherent in predictions of subsurface flow and transport. A typical PRA starts by identifying relevant components of a subsurface system (e.g., a buried solid-waste tank, an aquitard, a remediation effort) and proceeds by using uncertainty quantification techniques to estimate the probabilities of their failure. These probabilities are then combined by means of fault-tree analyses to yield probabilistic estimates of the risk of system failure (e.g., aquifer contamination). Since PRA relies on subjective probabilities, it is ideally suited for assimilation of expert judgment and causal relationships.