Stock market investing has emerged as a highly favored financial instrument in Indonesia; however, navigating the complexities of stock selection remains a formidable challenge, particularly for retail investors who lack specialized technical expertise in fundamental analysis. To bridge this critical gap, this study rigorously develops a robust Decision Support System (DSS) founded on the Multi-Attributive Border Approximation Area Comparison (MABAC) method. This research is highly significant as it represents the first documented application of the MABAC methodology for comprehensive stock evaluation and Stock Ranking within the dynamic and volatile environment of the Indonesia Stock Exchange (IDX). The evaluation framework utilizes five critical financial health indicators as criteria: Price to Earnings Ratio (PER), Price to Book Value (PBV), Return on Equity (ROE), Return on Assets (ROA), and Debt to Equity Ratio (DER). The system's performance was rigorously validated through an iterative process against manual calculations, yielding an exceptionally high consistency with a marginal average discrepancy of only 0.0001. The results specifically identify SIDO as the top-ranking stock, primarily due to its superior capability in maintaining high profitability while minimizing financial risk. Ultimately, this DSS furnishes investors with an objective, data-driven recommendation tool, establishing MABAC as a highly effective and reliable mechanism for enhancing the quality of investment decisions and mitigating financial risks in the Indonesian capital market.