A new logistic regression (LR) model was used to predict the probability of nitrate contamination exceeding 4 mg/L in predominantly shallow, recently recharged ground waters of the United States. The new model contains variables representing (1) N fertilizer loading (p < 0.001) , (2) percent cropland-pasture (p < 0.001), (3) natural log of human population density (p < 0.001), (4) percent well-drained soils (p < 0.001), (5) depth to the seasonally high water table (p <0.001), and (6) presence or absence of unconsolidated sand and gravel aquifers (p = 0.002). Observed and average predicted probabilities associated with deciles of risk are well correlated (r2 = 0.875), indicating that the LR model fits the data well. The likelihood of nitrate contamination is greater in areas with high N loading and well-drained surficial soils over unconsolidated sand and gravels. The LR model correctly predicted the status of nitrate contamination in 75% of wells in a validation data set. Considering all wells used in both calibration and validation, observed median nitrate concentration increased from 0.24 to 8.30 mg/L as the mapped probability of nitrate exceeding 4 mg/L increased from less than or equal to 0.17 to > 0.83.