This U.S. Geological Survey (USGS) data release represents tabular and geospatial data for the creation and application of a Bayesian network model that predicts Black Skimmer (Rynchops niger) and Gull-billed Tern (Gelochelidon nilotica) on bare ground sites across the U.S. portion of the Gulf of Mexico. Management plans with clear priorities can help to achieve Black Skimmer and Gull-billed Tern population targets (number of breeding pairs) because conservation and restoration opportunities can be limited and costly. These species form breeding colonies on bare ground sites, where the number of breeding pairs may be influenced by numerous site conditions such as site area, soil texture, and topography; island area, shrub area, and elevation; predators, and human disturbances. These data were used to develop a Bayesian network model that uses site conditions to predict Black Skimmer and Gull-billed Tern nest counts as a proxy for breeding pairs. We used the model and 2005-2015 bird survey data to estimate total nests and nest deficits for Gulf Coast Joint Venture Initiative Areas (IA) under existing conditions and simulated scenarios that presumed managers changed site conditions. We selected a best scenario for each IA based on its ability to simultaneously achieve both species targets for the least perceived effort. We used the best scenario to prioritize sites for management until the simulations suggested both species targets might be met. We then repeated the simulations while excluding sites that had attributes that limited their management application.