We combined statistical analyses and GIS capabilities within the statistical environment R to create a semi-automated method for the assessment of As hazard risk in shallow groundwater in Cambodia. Arsenic concentration data for groundwaters of between 16 and 100 m depth were obtained from 1437 geo-referenced wells. We created a binary logistic regression model with these As measurements as the dependent variable and a number of raster maps (DEM-parameters, remote sensing images and geomorphology) as explanatory variables, and considering an As threshold of 10 ppb. This allowed us to make an As hazard map for groundwaters between 16–100 m depth: this can be used to help to identify populations vulnerable to exposure. The logistic regression analysis indicates a good correlation between topographic and geomorphologic environmental variables and the As hazard risk in groundwater. Ease of implementation, and the ability to update, along with objectivity and reproducibility are the main advantages related to this method of analysis.