Groundwater contaminated with arsenic (As) threatens the health of more than 140 million people worldwide. Previous studies indicate that geology and sedimentary depositional environments are important factors controlling groundwater As contamination. The Mississippi River delta has broadly similar geology and sedimentary depositional environments to the large deltas in South and Southeast Asia, which are severely affected by geogenic As contamination and therefore may also be vulnerable to groundwater As contamination. In this study, logistic regression is used to develop a probability model based on surface hydrology, soil properties, geology, and sedimentary depositional environments. The model is calibrated using 3286 aggregated and binary-coded groundwater As concentration measurements from Bangladesh and verified using 78 As measurements from south Louisiana. The model's predictions are in good agreement with the known spatial distribution of groundwater As contamination of Bangladesh, and the predictions also indicate high risk of As contamination in shallow groundwater from Holocene sediments of south Louisiana. Furthermore, the model correctly predicted 79% of the existing shallow groundwater As measurements in the study region, indicating good performance of the model in predicting groundwater As contamination in shallow aquifers of south Louisiana.