In the face of rising defaults and limited studies on the prediction of financial distress in Morocco, this article aims to determine the most relevant predictors of financial distress and identify its optimal prediction models in a normal Moroccan economic context over two years. To achieve these objectives, logistic regression and neural networks are used based on financial ratios selected by lasso and stepwise techniques. Our empirical results highlight the significant role of predictors, namely interest to sales and return on assets in predicting financial distress. The results show that logistic regression models obtained by stepwise selection outperform the other models with an overall accuracy of 93.33% two years before financial distress and 95.00% one year prior to financial distress. Results also show that our models classify distressed SMEs better than healthy SMEs with type I errors lower than type II errors.

This paper aims to identify the determinants and predictors of Small and Medium-sized Enterprises (SMEs)’ financial failure. Within this framework, we have opted for a quantitative method based on a sample of healthy and failing SMEs of a Moroccan bank. The main results of the different optimal models are obtained by the stepwise method of estimating logistic regression. These results show, in a normal economic context, that the variables that discriminate between healthy and failing SMEs are the main predictors of financial failure. Autonomy ratio, interest to sales, asset turnover, days in accounts receivable, and duration of trade payables are the variables that increase the probability of financial failure, while repayment capacity and return on assets reduce the probability of failure. These variables present an overall classification rate of healthy and failing SMEs of 91.11% three years before failure and of 84.44% two years and one year before failure.

The absence of prior research in Morocco using the macroeconomic explanatory approach to bankruptcy, combined with the new peak in business failure in Morocco in 2021, motivates the need to explore the influence of macroeconomic indicators on the Moroccan bankruptcy rate. Therefore, the objective of this article is to examine the impact of these indicators on the Moroccan bankruptcy rate using multiple regression models over the period 2010-2021. The obtained results show that new firm creation and the interest rate positively and significantly affect the bankruptcy rate, while Euro and Dollar exchange rates have negative and significant effects on the dependent variable. The results suggest guidelines for policymakers and practitioners to refine the economic conditions in order to achieve a low bankruptcy rate in Morocco.