<![CDATA[This study aims to synthesize prior research on the application of the Grover G-Score model in predicting financial distress across various industry sectors and evaluate result consistency, with attention to its implications for the retail sector. Financial distress remains a critical early warning issue for management, investors, creditors, and regulators, yet no single prediction model has proven consistently superior across all industries. This research uses a qualitative approach through a narrative literature review. Five main articles published between 2020 and 2026, from the technology, agrifood, primary consumer goods, food and beverage, and retail sectors, were obtained from academic databases such as Google Scholar, Springer, and university journal portals, and analyzed through thematic analysis and comparative synthesis. The findings show that the Grover G-Score model performs relatively well in the technology, agrifood, and food and beverage sectors, even reaching an accuracy of 95 percent in food and beverage companies. However, its application to the retail sector remains inconsistent, since the Altman model was found more accurate than Grover in predicting financial distress among Indonesian retail companies. This inconsistency is attributed to retail-specific characteristics such as thin profit margins, high inventory dependency, and volatile daily cash flow, as well as differences in research period. The study concludes that Grover G-Score is useful for monitoring financial health but should not be the sole basis for decision-making in retail, and recommends combining it with other financial ratios and operational indicators such as inventory turnover and asset productivity.]]>
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