The article presents a global prediction map of groundwater arsenic concentrations exceeding 10 μg/L, created using a random forest machine learning model based on eleven geospatial environmental parameters and over 50,000 aggregated data points of measured groundwater arsenic concentration. The map includes known arsenic-affected areas and previously undocumented areas of concern. Combining the global arsenic prediction model with household groundwater-usage statistics, the authors estimate that 94-220 million people are potentially exposed to high arsenic concentrations in groundwater, with the majority (94%) being in Asia. The study highlights the importance of raising awareness, identifying areas for safe wells, and prioritizing testing to address this global health threat. Arsenic contamination is a significant issue due to its toxic effects on human health and wildlife, and the increasing reliance on groundwater to support growing populations and combat water scarcity. The model's performance is validated through a test dataset, showing high accuracy and sensitivity. The results emphasize the need for targeted surveys and mitigation measures, such as awareness campaigns, government support, health interventions, and alternative drinking water resources.The article presents a global prediction map of groundwater arsenic concentrations exceeding 10 μg/L, created using a random forest machine learning model based on eleven geospatial environmental parameters and over 50,000 aggregated data points of measured groundwater arsenic concentration. The map includes known arsenic-affected areas and previously undocumented areas of concern. Combining the global arsenic prediction model with household groundwater-usage statistics, the authors estimate that 94-220 million people are potentially exposed to high arsenic concentrations in groundwater, with the majority (94%) being in Asia. The study highlights the importance of raising awareness, identifying areas for safe wells, and prioritizing testing to address this global health threat. Arsenic contamination is a significant issue due to its toxic effects on human health and wildlife, and the increasing reliance on groundwater to support growing populations and combat water scarcity. The model's performance is validated through a test dataset, showing high accuracy and sensitivity. The results emphasize the need for targeted surveys and mitigation measures, such as awareness campaigns, government support, health interventions, and alternative drinking water resources.