LAUSR

After financial crisis of 2007-08, where many international corporations and financial institutions needed a bail out by government to remain in business, financial solvency and stability have become top most priorities for the financial sector globally (Chotalia, 2014). For this reason, Prediction of financial distress has gained a great deal of interest by researchers in finance recently (Al-Saleh & Al-Kandari, 2012). In view of this, there exist a large number of models and associated ratios propounded by various authors in predicting how healthy a company's financial condition is (Ahmed & Alam, 2015). However, the discriminant analysis as given by Altman is most effective and accurate among different techniques to predict financial distress (Bal, 2015). Accordingly, the purpose of this study was to evaluate financial distress conditions of selected Ethiopian micro finance institutions (MFIs) by applying Edward Altman’s revised Zscore model using secondary data for the period 2011 to 2015. To this end, the study revealed that 94 % of MFIs are in the safe zone and 6% in the grey zone among the selected institutions. The finding of the study also indicates fluctuation in Z-score of the institutions from period to period. In view of this, the paper is expected to be used as input for policy makers and practitioners as long as it provides empirical evidence on financial distress condition of MFIs. Moreover, along with the theoretical contribution, this study is expected to contribute insights for academicians as literature for further studies in the area of MFIs and state of financial distress.