Efforts to reintroduce and maintain populations of pronghorn (Antilocapra americana) to the California Central Valley, specifically the Carrizo Plain National Monument (CPNM) and the Mojave Desert (Antelope Valley) portion of Tejon Ranch, have largely been unsuccessful due to dwindling numbers of translocated animals. The objective of this study was to improve upon previous models for the CPNM using aerial survey data and then apply the model to the Tejon Ranch. Aerial survey data collected from 2000-2010 on the CPNM was used to establish “use” and “non-use” areas in the model. Model variables included vegetation type (forest, shrub, grassland, semi-desert scrub, crops, and bare areas), slope, and road density. Vegetation and road density variables were treated categorically and slope as a continuous variable. Kernel density estimation (KDE) was used to estimate utilization distributions and home ranges (Fieberg 2007). An 80% isopleth was used to define “used” and “unused” habitat areas within the study site. Binary logistic regression was used to detect correlations between habitat variables and habitat use by pronghorn. Results of the regression analysis indicated overall significance with a p-value of < 0.0001 (testing that all slopes = 0). Each habitat variable comparison was made after adjusting for the other variables (e.g., slope effects were evaluated after adjusting for road density and vegetation type) and was found to be significant. Each variable coefficient was then included in a predictive equation and entered into GIS to generate a map to predict where pronghorn would likely be observed. Similar layers were created for the Tejon Ranch and the predictive equation was run with the CPNM statistical analysis. Limited conclusions about habitat suitability on the CPNM or the Tejon Ranch can be made based on the habitat data available for this model. While slope, road density, and vegetation type are all significant habitat variables influencing pronghorn habitat use, further study is needed to understand the mechanisms driving these relationships. With additional data expansion of the current habitat suitability model would help to further define pronghorn habitat use, specifically the creation of a focused model of a particular season, life history period, or individual animal use to identify more detailed habitat use patterns.