In 2019, 254 samples were collected from five aquifer systems to evaluate per- and polyfluoroalkyl substance (PFAS) occurrence in groundwater used as a source of drinking water in the eastern United States. The samples were analyzed for 24 PFAS, major ions, nutrients, trace elements, dissolved organic carbon (DOC), volatile organic compounds (VOCs), pharmaceuticals, and tritium. Fourteen of the 24 PFAS were detected in groundwater, with 60% and 20% of public-supply and domestic wells, respectively, containing at least one PFAS detection. Concentrations of tritium, chloride, sulfate, DOC, and manganese+iron; percent urban land use within 500 m of the wells; and VOC and pharmaceutical detection frequencies were significantly higher in samples containing PFAS detections than in samples with no detections. Boosted Regression Tree models that consider 57 chemical and land-use variables show that tritium concentration, distance to the nearest fire-training area, percentage of urban land use, and DOC and VOC concentrations are the top five predictors of PFAS detections, consistent with hydrologic position, geochemistry, and land use being important controls on PFAS occurrence in groundwater. Model results indicate it may be possible to predict PFAS detections in groundwater using existing data sources.