This U.S. Geological Survey (USGS) data release represents data for the creation of a spatially explicit Bayesian network model that predicts Brown Pelican nests on islands across the U.S. portion of the Gulf of Mexico. Well-targeted management plans are needed to achieve Brown Pelican population objectives (number of breeding pairs) because conservation and restoration opportunities are limited and costly. To aid the design of such plans, we estimated population objectives for 10 U.S. Fish and Wildlife Service Gulf Coast Biological Planning Units (BPUs). We then developed a Bayesian network model that uses an island’s characteristics to predict pelican nest count, a proxy measure for breeding pairs. We used the model and 2000-2015 bird survey data to estimate each BPU’s total nest count given the existing islands’ characteristics. We then used the model to hypothesize island-specific actions and simulate management scenarios that implemented these actions opportunistically (randomly selected islands) or strategically (target islands with the highest nest count) until the population objective was met. We then estimated each BPU’s (1) total number of islands; (2) total nesting, roosting, and loafing habitat needed to achieve its population objective (habitat objective); and (3) the effort required to achieve the habitat objective (management efficiency).