In this study risk assessment is carried out to estimate the probability and magnitude of risk due to the unexpected system failure by considering different repair assumptions for repairable system. In order to measure the risk for different repair assumptions, the probability of failures and consequences are required. The probability of failure estimated using parametric Recurrent Data Analysis (RDA) approach while the consequences of failure analyzed based on reported data. Gas Turbine (GT) system was taken as a case study to verify the model. The results indicated that perfect repair assumption leads to minimum risk compared to imperfect and minimal repair assumptions. Based on results it was concluded that the maintenance team needs to follow perfect repair to mitigate the risk each time a failure happens. © Maxwell Scientific Organization, 2014.