Abstarct: Banks and financial institutions give their customers loans under some conditions, always. customers can be divided in to three groups baxsed on their performance. The first group of customers cut off their relationship with the bank, completely. This group of customers are called dishonest which their survival time to repay the loan is equal to zero. The second group is those customers who do not care about their loan repayment. Contrary to the first group, they repay their loan somedeal and then cut off. This group has positive survival time of repayment of loan, but finally they are turned to dishonest one. We call these customers defaulter. At last, the third group is the customers who repay their loan in a timely manner. In order to maximize the profit of a bank, it is necessary to minimize the rates of dishonest and defaulter customers and maximize good customers (the third group). Therefore, analyzing the survival time of loan repayment can be vital in any bank. Analyzing of the timelength of the data till the occurance of a phenomenon (here, repayment of loan) places in the survival analysis domain. In the analysis of the survival data, the main problem is to find a suitable model for measuring the affection of the various factors on the length of the survival time. Accordingly to the nature of the data attained from the bank customers, the survival of non-repayment of dishonest and defaulter customers do not tend to zero. A suitable category for these type of the survival data is Healing rate models. For these models, two subclasses are introduced: mixture and non-mixture models. There is a problem with using of the Healing rate models for analyzing the borrowers behaviour, and that is the first group of customers which their survival repayment tend to zero. This case causes an unwanted fitness in the Healing rate model. In such cases, it is recommended to use zero-inflated models. In this thesis, first we introduce the zero-inflated rate model and then it for data analysis we will refund some of our clients to four types of registered banks in the central bank of Iran.