Greater sage-grouse (GSG; Centrocercus urophasianus) selectively utilize portions of sagebrush and sagebrush associated habitats within broad and heterogeneous landscapes. Until recently, sage-grouse research has generally focused on fine-scale vegetation structure and composition and less on landscape-scale habitat requirements. Insufficient information at broad scales limits a manager’s ability to interpret and predict habitat use patterns, assess habitat suitability, and target areas for conservation and ecological rehabilitation. We identified environmental attributes associated with GSG habitat use at broad spatial scales. In 2006, we captured 50 GSG, radio-collared each bird, and tracked each bird’s position within a 31,416 ha study area in central Oregon, USA. We monitored birds year-long between March 2006 and March 2008 across the study area. Each time a bird was located, we collected a coordinate position at the point where it was observed. We generated spatially explicit predictor variables in a Geographic Information System to quantify the association between landscape structure and GSG occurrence. Predictor variables included elevation, slope, aspect, curvature, solar radiation, landscape ruggedness, orientation, distance from roads, distance from leks, distance from mesic habitats, and cover type. We used spatial modeling (Maximum Entropy) to 1) develop predictive models of GSG seasonal resource use, 2) generate probability maps for visual assessment, and 3) characterize response curves associated with GSG habitat preference based on individual landscape predictor variables. Results indicate that during the breeding season GSG will use big sagebrush, low sagebrush or complexes of low and mountain big sagebrush cover types. During the summer season, GSG use low sagebrush, mountain big sagebrush, and mesic areas. Additionally, summer season use areas include higher elevation sites within or in close proximity to habitats that sustain succulent forbs throughout most of the growing season. Maps of modeled data identify spatially explicit areas of preferred habitat and predicted bird use patterns. This information can help managers identify and protect important GSG habitat across heterogeneous landscapes.