The Johnson-Ettinger Model is widely used for assessing the impacts of contaminated vapors on residential air quality. Typical use of this model relies on a suite of estimated data, with few site-specific measurements. Software was developed to provide the public with automated uncertainty analysis applied to the model. An uncertainty analysis was performed on the model, that accounted for synergistic effects among variable model parameters. This analysis showed that a simple one-at-a time parameter uncertainty analysis provides a rough guide for the uncertainty generated by individual parameters and allowed their ranking. The one-at-a-time analysis, however, underestimated the uncertainty in the model results when all or groups of parameters were assumed to be uncertain. An apparent increase in simulated cancer risk caused by the uncertainty introduced from the input parameters was as much as 1285%. The model response to the input parameters showed that for the example studied, there was a positive skew in the model response to parameter variation.