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Lebanon is currently witnessing the most severe banking sector crisis in its history. Thus, nowadays, the demand for financial analyses in banks has increased to examine the financial distress and the potential impact of the macroeconomic factors. Consequently, this research studies bank distress in Lebanese Alpha banks and addresses the question of how the Lebanese major macroeconomic factors affect it. The researchers calculated the mean Altman Z”-scores for 10 Lebanese Alpha banks for the period 2009 – 2018 as an indicator for financial distress. Furthermore, they collected data regarding the chosen macroeconomic indicators for the same period from the World Bank Data. Consequently, the researchers developed a Regression Model and analyzed the model and a multicollinearity test. The calculated Altman Z"-scores showed that Lebanese Alpha banks were very likely to be financially distressed. Moreover, the results showed that there is a positive relationship between debt service, government expenditures, unemployment, and the real interest rate on one side and alpha banks’ high probability to become distressed on the other side. First, gathering data regarding the macroeconomic indicators was a hurdle as there were differences among the sources (Lebanese Ministry of Finance, BDL, Bloomberg, IMF, and World Bank). This is why the authors depended on the values published by the World Bank Data as a reliable source. Second, there is a lack of studies analyzing the relationship between the banking sector’s current crisis and the individual macroeconomic variables. However, this limitation also gives value to the results of this study. This research sheds light on the significance of the Altman Z"-score as an indicator for financial distress in Lebanese Alpha banks. Thus, a model can be developed based on the basic Altman model that fits for Lebanese banks. Moreover, banking authorities (BdL, ABL, and BCC) should impose yearly calculations of this score to detect probable future distress. The value of this study stems from it being one of the first studies in the Lebanese market examining the impact of macroeconomic factors on the Z”-scores of the Lebanese Alpha banks using the Multiple Regression Model.