Financial distress is a significant challenge for companies worldwide, yet comprehensive research on its determinants, particularly in emerging countries like Malaysia, remains limited. This study addresses this gap by investigating financial distress among ACE Market companies listed in Bursa Malaysia. This study utilized the quantitative data sourced from Refinitiv DataStream and Bursa Malaysia’s annual reports. This study analysed the relationship between firm characteristics and the likelihood of financial distress measured by Z-score. For the likelihood analysis of financial distress, this study applied logistic (logit) regression. The findings for logistic regression results confirm that efficiency, asset tangibility, market value, and firm size significantly predict financial distress. Logistic regression results substantiate some of these findings, indicating that efficiency, asset tangibility, market value, and firm size significantly affect the likelihood of financial distress, while profitability, liquidity, leverage, and growth show varying degrees of significance. These findings guide financial managers to effectively reduce the risk of financial distress and further offer valuable insights for stakeholders and policymakers, strategic planning, and policy formulation in challenging business environments.