This study aims to investigate determinants of the probability of default on agricultural facilities granted to 286 companies during the years 2007 to 2017. Logit, Probit, and C-Log-Log models have been used for this purpose. The variables included the relevance of the CEO’s field of study; a single beneficiary company, domestic production of raw materials and Altman Z- score or company’s financial strength. The results reveal the high validity and strength of the Probit model, as it can predict and classify observations with high probability of default with 96% accuracy and observations with low probability of default with 92% accuracy, which can demonstrate the validity of the model. The results also show that the probability of default is chiefly affected by a company’s financial strength. Therefore, in order to significantly reduce the probability of default in repayment of the facilities granted by customers, greater attention should be allocated to the financial strength of companies at the time of granting facilities.

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