Crop residues can make a significant contribution to the energy sector in Kenya. The purpose of this study was to identify the availability and spatial distribution of crop residues and their energy potential through the creation of a Geographical Information System (GIS) model. This information is important to the successful utilisation of these residues. In addition, a GIS tool was created that automates the resource estimation process for the purpose of identifying potential biomass energy plant sites. This study was conducted considering six provinces: Rift Valley, Western, Nyanza, Eastern, Central and Coast. The Rift Valley Province was selected as the case study for model tool creation and the crops considered in the study were maize, wheat, rice and sugarcane. The study was a quantitative one entailing the collection of secondary data in the form of crop production statistics and spatial data which comprised population, land use and road shape files and analysis using GIS. Residues to Product Ratios were used to estimate the amount of crop residues while Lower Heating Values assessed the energy potential. Moreover, ArcGIS Model Builder was used to create the GIS model tool for the feasibility of a potential biomass energy plant. The results of this study indicated the amount of crop residues that can be generated in Kenya to be about 7,384,600 tonnes with an energy potential of approximately 124,300 TJ/year. Rift Valley Province was found to have the highest residue generation of about 3,866,000 tonnes with a corresponding energy potential of about 64,800 TJ/year. The GIS model showed that the Rift Valley Province and Uasin Gishu, Trans Nzoia, and Nandi districts all had the potential for high residue generation resulting from their high agricultural production and high yields. The modelling tool was also able to demonstrate the increase in the amount of crop residues that can be collected using different radii around a potential biomass plant. The main conclusion was that crop residues have a high potential for energy generation in Kenya. In addition, a GIS model tool was created for Rift Valley Province which can be transferred to any other region, in order for the local energy planners to supply the model with their own parameters to obtain locally based results.