Cloud computing has emerged as a transformative solution across various industries, offering scalable infrastructure, improved efficiency, and potential cost savings. However, determining whether to migrate to the cloud requires a careful evaluation of both tangible and intangible factors. This study presents a mathematical model to conduct a structured cost-benefit analysis for cloud migration, specifically tailored to the manufacturing and healthcare sectors. The model incorporates variables such as initial investment, operational expenditure, downtime risk, data sensitivity, compliance requirements, and expected return on investment. Distinct parameters relevant to each industry are considered such as production cycle disruptions in manufacturing and patient data security in healthcare. By applying optimization techniques and comparative analysis, the model assists stakeholders in making data-driven decisions about cloud adoption. The findings highlight critical cost thresholds and strategic considerations that influence migration feasibility. This research not only provides a quantitative framework for evaluating cloud migration but also contributes to better resource planning and technology adoption in sectors with complex operational and regulatory demands.