Since the commencement of Kenya's Strategic Plan, Vision 2030, in 2008, the country has seen a significant expansion in the number of universities, particularly private universities as opposed to public universities. By 2023, there were 33 private universities, up from 12 in 2008. Over the same time period, the proportion of rise in student enrolment has not kept pace with growth, owing to the constraints imposed by University entry grades and credentials criteria. Globally, private higher education remains the fastest-growing sector of higher education. The result has been intense competition, threatening the viability and profitability of many private universities. The study sought to assess the impact of cost leadership strategic strategies on the performance of private universities and was a case study of Gretsa University, a private university in Kenya. The study's aims were to determine the impact of pricing strategy, operating strategy, and integration strategy on the performance of private institutions in Kenya. The Resource Based View Theory, the Dynamic Capabilities Theory, and Michael Porter's Industrial Forces model served as the study's framework. A descriptive research design was used with a quantitative methodology. Primary data was obtained based on a census of the whole population of 19 top managers who were designated as the ones in charge of strategy formulation and implementation. They comprised academic and non-academic department leaders, as well as the university's top executives. The data was collected using a self-administered semi-structured questionnaire. The data gathering items contained both closed-ended and open-ended inquiries. To address the research questions, the data was analysed using a quantitative data analysis methodology and tools, and the results were presented as descriptive and inferential statistics. The study discovered a correlation value (R=0.892), indicating a high relationship between the predictors (cost leadership strategy approaches - pricing, operational and vertical integration strategies) and the dependent variable (performance of private institutions in Kenya). The coefficient of determination (R2=0.751) indicated that the model explained 75.1% of the variation or change seen in University Performance. This study recommended fully owning the supply chain to eliminate middlemen such as student enrolment agencies and bodies, maximizing technological adoption by fully digitizing all student life processes, and bundling short courses with main courses, all while maintaining quality services and avoiding cuts in critical areas such as innovation, research, and customer service. Additional research should look into additional factors that may influence the performance of private universities in Kenya.