A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.