This research project has resulted in a thorough understanding of the factors affecting PV farm siting, as well as the use of logistic regression to develop a valid model incorporating the most significant siting factors to predict the likelihood or suitability for PV siting at a given location. This model was then applied within ArcMap to create a suitability map for PV siting across the entirety of Ontario, using raster calculator to mimic the determined logistic regression expression. It is also expected that this model is able to be applied to other study areas and obtain similar results, given that data about the significant siting factors is available for that study area. There are some limitations to the model’s applicability, in that it does not take into account varying insolation rates, and that some of the categorical factors could vary largely given a different study area (Land class/use, soil drainage, etc.). The model performance also depends on the extent of the siting factor data, and performs poorly in areas that contain gaps in data such as northern Ontario, however the model is an excellent parameter for PV farm siting suitability when used in areas that contain continuous data for each of the chosen siting factors. Recommendations for future use of this model would be to attempt the same method of analysis in a location with similar parameters to Ontario to further confirm the model’s validity, as well as attempting the same research workflow in a location with vastly different geography, such as a desert or mountainous region, to analyze how the factors significance varies and to identify and investigate new factors not included within this research study.