Credit risk is due to that recipients of the facility, deliberately or involuntarily, don’t have ability to repay their debts to the banking system that this risk is critical in Iran compared to the global. Therefore, the purpose of this study was to investigate the effect of macroeconomic variables on credit risk of Iranian banking industry during the 2006-2016 years and also simulation and prediction of credit risk situation in 2017 under different stress scenarios, bu using stress test. Data used in this research is time series and seasonal. In order to implement a stress test and achieve the purpose of the research, first, the effective macroeconomic variables and the rate of each onechr('39')s influence on the credit risk are determined using Auto-Regressive Distributed Lags (ARDL). Accordingly, the inflation rate, exchange rate, unemployment rate and housing index in total have a positive effect and variables GDP, the interest rate of bank facilities and the volume of concessional facilities to both government and non-governmental sectors, have a negative impact on credit risk. In the following, using the stress test, simulation of critical situations and prediction of credit risk values in 2017. This was done in three scenarios with titles of mild stress, extreme stress, and hyperstress that in each scenario, different shocks are applied to the variables affecting credit risk. The results of the stress test and scenarios show that the compulsory reduction of interest rates on bank facilities in all three scenarios, initially in the second quarter of  2017, leads to a reduction in credit risk, but rising exchange rates, rising inflation, falling economic growth, as well as accumulation of past values of credit risk, has led to a rapid increase in credit risk and also in scenarios with more severs shocks, has led to catastrophic increase of credit risk in later periods in all scenarios.