This project aimed at determining if Altman Z” (1993) can accurately forecast the failure of non-financial firms listed on Nairobi Securities Exchange (NSE). The study was anchored on entropy, credit risk, cash management and Gamblers ruin theory. A descriptive study approach was used, as well as a purposive sampling technique. The study looked at 46 non-financial enterprises listed on the NSE from 2016-2020. The secondary data used in the analysis came from audited financial statements published NSE and Capital Markets Authority websites. SPSS version 21 and Microsoft excel were employed in analysing the data that had been collected. The data was presented in tabular and figurative form. The empirical results revealed that the model predictive accuracy for distressed and non- distressed companies was 100% and 80.6% respectively. Overall, the model correctly categorized 39 out of 46 companies as either financially distressed or not, resulting in an 84.8 % overall accuracy rate. The research also revealed that the four ratios of the model had an impact which was both positive and statistically significant in predicting financial distress for listed non-financial entities. This study recommends employing Altman Z” (1993) to detect financial distress in non-financial companies early, to ensure that corrective actions are taken in a timely manner. Non-financial company management in Kenya should also develop a working capital management policy that will ensure that current liabilities are kept below current assets at all times, focus on increasing operational efficiency and lowering sales costs and operational costs, which will increase their EBIT and prudent borrowing and liability management, which will likely decrease the likelihood of insolvency. The research in addition, helps add to the body of knowledge by by expanding discussion on use of Revised Altman Z”-Score model both in developed and developing countries. The research also expands on existing theories and empirical studies on financial distress by providing valuable information on the subject in regard to the Kenyan context.

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