Clean technologies aim to address climatic, environmental, and health concerns associated with their conventional counterparts. However, such technologies achieve these goals only if they are adopted by users and effectively replace conventional practices. Despite the important role that users play to accomplish these goals by making decisions whether to adopt such clean alternatives or not, currently there is no systematic framework for quantitative integration of the behavioral motivations of users during the design process for these technologies. In this study, the Theory of Planned Behavior (TPB) is integrated with Usage-Context Based Design to provide a holistic approach for predicting the market share of clean versus conventional product alternatives based on users’ personal beliefs, social norms, and perception of behavioral control. Based on the mathematical linkage of the model components, technology design attributes can then be adjusted, resulting in the design of products that are more in line with users’ behavioral intentions, which can lead to higher adoption rates. The developed framework is applied in a case study of adoption of improved cookstoves in a community in Northern Uganda. Results indicate that incorporating TPB attributes into utility functions improves the prediction power of the model and that the attributes that users in the subject community prioritize in a clean cookstove are elicited through the TPB methodology. Households’ decision-making behavior before and after a trial period suggests that design and marketing strategy should systematically integrate users prior to interventions to improve the outcomes of clean technology implementation projects.