Small and Medium Enterprises (SMEs) face numerous challenges in identification, setting up and making use of Information Technology (IT) as an enabler for business. Cloud computing could solve this problem by offering ready, low cost of entry IT solutions. Adoption of cloud computing among the SMEs in developing countries is however low due to a number of barriers as identified by previous studies. Over the years, research on adoption on innovation and technology has unveiled a number of theories on adoption which range from Individual level theories to Organizational level theories and even Market level theories. This study reviews the various theories, opting to use an organization level theory so that focus on the SME is emphasized. Analysis of literature renders this study to be based on the Technology-Organization-Environment (TOE) framework. This study reviews the current adoption levels of cloud computing and proposes a TOE based model for adoption of cloud-based services by SMEs in developing countries. The study employed literature review to determine the factors that are applicable for a model on adoption of cloud computing in the developing countries. Further, the study conducted a survey through a questionnaire to collect quantitative data to assist in determination of the most applicable model. Convenience sampling was employed. The study findings revealed that there is low adoption of cloud computing for business applications by SMEs in Nairobi County, hence confirms the need for the adoption model. Using Exploratory Factor Analysis (EFA) six components were extracted for the proposed model which include Relative Advantage, Accessibility, Organization Readiness and Size, Vendor Readiness, Regulations and Trading Partner Pressure, each with attributes required to ensure successful adoption of cloud computing. The model was validated through statistical analysis which confirms a largely reasonable level of fit for the indices and construct validity conducted through convergent and discriminant validity methods. Further, the model was subjected to experts’ analysis who concluded that the model is simple, applicable and fitting. The study finally proposes practical recommendations to governments and policy makers, educational institutions, software vendors and SMEs based on the model. Further research areas include subjecting the model to larger sample sizes to confirm its validity and the preparation of an implementation guideline.