The transition to renewable energy sources (RES) for electricity generation has gained significant momentum due to environmental and sustainability concerns. However, the high initial costs associated with RES implementation remain a critical barrier, particularly for micro, small, and medium enterprises (MSMEs). To address this challenge, a cost-effective optimization framework for the hybrid renewable energy system (HRES) was proposed, integrating advanced decision-making methodologies. The study focused on a case study of an MSME in a rural village in Ludhiana, Punjab, where the feasibility of various HRES configurations was evaluated using HOMER Pro software. The optimization process aims to minimize key financial metrics, including net present cost (NPC), operation and maintenance (O&M) costs, and the levelized cost of energy (LCOE), while simultaneously reducing carbon emissions. Sensitivity analyses were conducted to assess the impact of critical parameters such as diesel prices, inflation rates, and system constraints. To rank the HRES configurations, a multi-criteria decision-making (MCDM) approach is employed, combining the Method based on the Removal Effects of Criteria (MEREC) for weight determination and the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) for system ranking. The results demonstrate that the proposed framework effectively identifies the most cost-effective and environmentally sustainable HRES configuration, providing a robust decision-making tool for MSMEs. This study not only contributes to the growing body of knowledge on RES optimization but also offers practical insights for policymakers and stakeholders aiming to promote renewable energy adoption in small-scale industrial settings.