Recorded severity of grape powdery mildew on berries of untreated, susceptible hybrid cultivars varied from 0.2 to 50.5% across a 30-year period in Geneva, NY; within 7 of those years, cluster disease severity ranged from 3.42 to 99.5% on Vitis vinifera 'Chardonnay'. Although existing temperature-driven risk models could not account for this annual variation, pan evaporation (Epan), an environmental variable influenced by the collective effects of temperature, vapor pressure deficit, solar radiation, and wind speed, did. Logistic regression analysis (LRA) was used to classify epidemics as either mild or severe. Recursive partition analysis (RPA) provided a simplified decision tree for calculation of powdery mildew risk and incorporated (i) an estimate of the relative primary inoculum levels based on temperatures in the previous late summer and (ii) the current season favorability for pathogen development during the grapevine phenological period critical for berry infection by Erysiphe necator. Although the LRA had fewer instances of misclassification, RPA provided a rapid means for seasonal risk classification. Both the RPA and LRA models are able to describe disease severity risk in real time or can be used to forecast risk, thereby allowing growers to adjust management programs in a responsive manner.