A prototype of a predictive model for estimating chemical permeation through protective clothing materials was refined and tested. The model applies Fickian diffusion theory and predicts permeation rates and cumulative permeation as a function of time for five materials: butyl rubber, low density polyethylene, natural rubber, neoprene, and nitrile rubber. The model provides two approaches to estimate the solubility, one using a group contribution approach (UNIFAP S) and the second using an equation of state approach (EOS S). The model provides one approach to estimate the diffusion coefficient (CORR D). Refinement of the model was investigated through a preliminary analysis of the concentration dependence of the diffusion coefficient. A finite difference technique was developed and, for 50% of the cases analyzed, the permeation-time behavior could be described more accurately assuming concentration dependence. No correlation, however, was identified to apply this finding in a predictive mode. Correlations developed previously to estimate constant D values (CORR D) were refined using a larger data set. The accuracy and limitations of the refined model were evaluated by comparing model predictions with literature data. Overall, the accuracy of the model is fair; for 200 data sets representing a range of chemical types, 70-80% of the predicted permeation rates were within an order of magnitude of the measured values. The UNIFAP S/CORR D approach was more accurate than the EOS S/CORR D approach, however, the former could not be applied in many cases because UNIFAP parameters are not available for all functional groups.