Models were developed to predict spatial distribution of prehistoric archaeological site potential in the Sawtooth National Forest. Archaeological data and environmental parameters were collected and processed in a GIS. Predictor variables were evaluated to discover correlates with human locational behavior & compared against a control dataset. Three modeling methods were used: Logistic Regression, Regression Tree, and Random Forest. These models were assessed for efficacy using k-fold cross-validation and gain statistics. Although observed relationships could result from biases in archaeological data and predictors, results suggest a strong correlation between environment and prehistoric site location.