The share of developing countries in the global software market has risen and now accounts for around 5 percent of sales. A small number of developing countries have successfully developed their own software industries and have continued to strengthen the sector even after 2000. However, many customers in Kenya frequently opt for better packaged and marketed software from India, United State or Unite Kingdom, even when these have to be overhauled to suit the Kenyan market. In doing so, the customers deny the local products the much needed breathe of life that is required to enable them to survive in the competitive software marketplace. Relatively little research has examined a model for the adoption of local software, either as a unique task or in the context of local software development in Kenya. This study attempted to explain how adoption of local software development is affected by the individual, technological, environmental and organizational determinants in Kenya. In this framework, explanatory research design was used. The population for this study was the 347 Information Technology and Information Communication Technology companies which provide software services in Kenya and their customers/users. The list was obtained from members of Kenya Information Communication Technology Providers Association. A sample of 35 managers from firms was taken and also 70 users. Purposive sampling was applied to select the product managers while random sampling was used to select the 70 customers. In this study, primary data was collected using a structured questionnaire. The researcher used Statistical Package for Social Sciences Version 20 (SPSS) to generate the descriptive statistics and inferential results. Confirmatory Factor Analysis was used to analyze the data and Structural Equation Modeling using Analysis of Moment Structures was used to validate the research model. Post study interview was carried out to test the applicability of the model. Data collected from interview was analyzed and presented using content analysis. The expected results include a model that can used to enhance adoption of local software. The study findings indicated that there was low level of local software adoption. Results further indicated that individual factors, technological factors, organizational factors and environmental factors were negatively correlated with adoption of local software adoption.