The paper presents a statistical evaluation of three highway air pollution models (CALINE 3, HIWAY-2, and ROADWAY) using the tracer data from the General Motors Sulfate Dispersion Experiment. The bootstrap resampling procedure is used to quantify the variability in the observed concentrations due to the stochastic nature of the atmosphere. The results suggest that the variability in the observations due to the random nature of the atmosphere is about 30%. Therefore, if the predicted values are within 30% of the measured concentrations, the differences between model predictions and observations should not be considered to be significant. Comparisons of the model predictions paired and unpaired in time with measurements suggest that HIWAY-2 and ROADWAY perform best, but the performance of CALINE 3 is acceptable. Application of the extreme value theory and the bootstrap resampling procedure to the modeled and measured data (unpaired) shows that all three models are capable of predicting the extreme concentrations within the model performance criteria set forth above.