In Reliability/Availability(R/A) analysis, operating time prediction plays one of the major key roles to availability forecasts which are based solely on the past operating experience. Statistical prdiction of operating time of the nuclear reactor and the knowledge of the interrelationships betwen the explanatory variables and the response variable are essential to the evaluation of availability of the existing nuclear power plant. In addition, these informations are usdful for an evaluation of maintenance policy, for component replacement policy and for readiness of the nuclear power plant. Multiple linear regression analysis enables a decision maker to predict future operating times under given conditions. In addition, it is possible to assess various factors influencing nuclear power plant operating characteristics. In this paper, it is investigatexplanatory variables an the response variable form the operating history data and seven multiple linear regression models are developed in sequence to see the trend of model explanability. This approach was verified over the past data and compared with time series analysis. The results showed that until observation number around 60, it is well predicted but thereafter the deviation increased. The correlation coefficient between the observed and the predicted values was 0.6992. This implies tht multiple linear regression analysis is an effective approach to operating time prediction.