Arsenic contamination in groundwater is a global health issue affecting millions of people, particularly in Asia. A global prediction map of groundwater arsenic concentrations exceeding 10 µg/L was created using a random forest machine learning model based on geospatial data and over 50,000 measured data points. The map identifies both known and previously undocumented areas of concern. Combining this with household groundwater usage data, it is estimated that 94-220 million people are at risk, with 94% in Asia. Groundwater is increasingly used to meet growing water demands, making this issue critical for awareness and testing. Arsenic, a naturally occurring element, is toxic and can cause health problems such as skin disorders, cancer, and neurological issues. It enters groundwater through geological processes, particularly in alluvial sediments under anoxic or oxidizing conditions. Climate and soil parameters are key factors in arsenic release, with precipitation and evapotranspiration playing significant roles. The global model, developed using 11 predictor variables, shows high accuracy (AUC 0.89) and is used to identify high-risk areas. The model's results indicate that 94-220 million people are potentially exposed to high arsenic concentrations, with most in South Asia. The study highlights the need for targeted testing and mitigation strategies, especially as groundwater use increases. The model's accuracy is supported by previous studies, and it provides a detailed global view of arsenic contamination. However, the model's predictions are based on available data and may not account for local variations. The study emphasizes the importance of further research and testing to address the global arsenic threat.Arsenic contamination in groundwater is a global health issue affecting millions of people, particularly in Asia. A global prediction map of groundwater arsenic concentrations exceeding 10 µg/L was created using a random forest machine learning model based on geospatial data and over 50,000 measured data points. The map identifies both known and previously undocumented areas of concern. Combining this with household groundwater usage data, it is estimated that 94-220 million people are at risk, with 94% in Asia. Groundwater is increasingly used to meet growing water demands, making this issue critical for awareness and testing. Arsenic, a naturally occurring element, is toxic and can cause health problems such as skin disorders, cancer, and neurological issues. It enters groundwater through geological processes, particularly in alluvial sediments under anoxic or oxidizing conditions. Climate and soil parameters are key factors in arsenic release, with precipitation and evapotranspiration playing significant roles. The global model, developed using 11 predictor variables, shows high accuracy (AUC 0.89) and is used to identify high-risk areas. The model's results indicate that 94-220 million people are potentially exposed to high arsenic concentrations, with most in South Asia. The study highlights the need for targeted testing and mitigation strategies, especially as groundwater use increases. The model's accuracy is supported by previous studies, and it provides a detailed global view of arsenic contamination. However, the model's predictions are based on available data and may not account for local variations. The study emphasizes the importance of further research and testing to address the global arsenic threat.