Wind and other energy development are expanding rapidly and on an unprecedented scale within the range of the Golden Eagle (Aquila chrysaetos) while other anthropogenic-related changes, wildfires, invasive plants, drought, and climate change are altering or destroying native habitats occupied by Golden Eagles. However, the potential effects of these factors on North American Golden Eagle populations are largely unknown and the most recent evidence indicates that the population in the western United States is declining slightly. Impediments to evaluating the potential effects of energy development projects on wintering Golden Eagles include issues of scale and a paucity of available information about eagle winter use areas and ecology. We applied a predictive model of eagle winter distribution developed for Idaho and Montana, to Idaho, Utah, Nevada and eastern Oregon to help identify potential wintering areas and identify risks that occur in those areas. The model identifies ~40% of the four state study area as potentially suitable eagle winter habitat and provides a basis for spatial assessment of possible risk factors to eagles wintering there. We used eBird and Christmas Bird Count citizen science datasets for an independent evaluation of the accuracy of our predictive distribution model. The model was robust, accurately predicting the presence of wintering Golden Eagles significantly more often than expected. We used digital environmental datasets (layers) of potential risk factors, in conjunction with model predicted eagle distribution, to better understand and estimate the extent of risks to the wintering eagle population in the study area. These layers represent available data for some of the factors previously identified as risks in the landscape to wintering Golden Eagles. The majority of predicted eagle wintering areas occurred where there was little habitat fragmentation (<10%). All predicted winter areas contained at least one potential risk factor (e.g., potential for energy development); 39.4% of predicted winter areas contained at least two known risk factors. The greatest number of risks often occurred where the human footprint was highest and where eagles were less likely to occur during winter. Our results can be used to help prioritize field surveys for identifying important Golden Eagle winter areas in the western United States and determine potential locations where energy development is least likely to have negative effects on wintering eagles. Survey efforts can be allocated in consideration of management and conservation objectives based on predicted habitat suitability and risk factors. For example, surveys for areas of high suitability and low risk can identify places to focus management for conservation of eagle winter areas. Further, sites proposed for wind energy development could be reviewed initially based on model predicted eagle wintering areas and then surveyed to determine if permitting for development is appropriate.