Policy Capturing, a potential methodology for evaluating landscape preference, was described and tested. This methodology, tested and applied in industrial psychology since 1960, results in a mathematical model that theoretically represents the human decision-making process. Under experimental conditions, judges were asked to express their preferences for scenes of the Blue Ridge Parkway (Virginia and North Carolina). A multivariate linear model simulating each judge's decision was computed by regressing landscape preferences onto 10 dimensions thought to influence such preferences. An equation which "captures," or defines the policy of each judge was generated. Individual equations were then clustered and a composite strategy calculated at each step until one overall policy was obtained. Coefficients of determination (R²'s) for some individuals were generally large (>0.50). However, composite R²'s were fairly low (<0.25). Methodological problems concerning the use of policy capturing for landscape assessment along with practical management applications are discussed.