Financial Distress Prediction Models: A Case of Zimbabwean Manufacturing Companies

 The aim of the study was to develop a model that predicts financial failure of manufacturing companies in Zimbabwe using Altman Z-Score, Logistics Regression and Multivariate Discriminant Analysis. The research used a sample of nine (9) ZSE listed manufacturing companies over a four year period (2017-2020) using Multivariate Discriminant Analysis , logistics regression and Altman Z-Score methods. The findings from Multivariate Discriminant Analysis (MDA) show that Eleven (11) (64.7%) cases were correctly classified under distressed group and fifteen (15) (88.2%) cases were correctly classified under not distressed group and 50% fairly well group. Generally the financial ratios helped to classify 64.7% of the cases correctly in distressed status and 88.2% of the cases correctly into not distressed status and 50% in the fairly well group. This shows that the financial ratios as independent variables or discriminators they have more predictor power on classifying distressed manufacturing companies than not distressed manufacturing companies in Zimbabwe. The findings show that, based on the omnibus tests of model significance , the model is valid and significant. The Hosmer-Lemeshow tests revealed a nonsignificant chi-square (0.56) indicating that the data f it the model well. With the independent variables added, the model correctly classifies 77.8% of cases overall. Therefore, 88.9% of participants who were originally classified as distressed were also predicted by the model to be distressed. Furthermore, 66.7% of participants who were not distressed were correctly predicted by the model to have no distress. From these f indings Sales to Total Assets and constant added significantly to the model/prediction. In conclusion, the Altman Z-Score agreed with most of the events that took place during the period 2017-2020, therefore, correctly classified 77.78% of the total cases. The merit of the Altman Z-Score is that it shows the trend or transition of the entity through the distress, grey and safe zones. the Multivariate Discriminant Analysis had the lowest predicted cases correctly classified while logistic regression had the highest. The MDA has discriminant function, logistics regression has a regression equation, while Altman Z-Score has a formula. The study recommends that the Altman Z-Score needs to include other financial distress ratios, than to be limited to its five key ratios, the multivariate discriminant analysis should show f irm specific and industry output in singular and combined years for proper decision-making process and logistic regression can be improved to solve non-linear problems.