Financial Service Providers (FSPs) like other organizations can use ‎Customer Lifetime Value (CLV) as an instrument to achieve their targets in ‎Customer Relationship Management (CRM). Although various studies have ‎been done about this concept, CLV case studies are scarce in banking ‎industry. In this research, in order to present a model to determine CLV in ‎banking industry, customers with current account in a bank in Iran were ‎studied. Determining the relative importance of R, F and M variables that are ‎used to cluster customers, ranking the clusters of customers according to ‎their CLV and understanding the best strategies for bank to treat with each ‎cluster are among the other goals of this study. Three main variables were ‎used to apply the model; a) Recency: the length of time since the last ‎transaction (in days), b) Frequency: number of positive transactions and c) ‎Monetary: balance of account (in Rials). Also wR , wF and wM were used as ‎the relative importance of R,F and M variables. We used the ideas of experts ‎and marketing managers and the data of transactions from the random ‎samples of 382 corporate customers and 5113 individual customers, who had ‎current account in 33 branches of a bank in Tehran. The analytical Hierarchy ‎Process (AHP) was applied to determine wR , wF and wM in evaluating CLV. ‎Then WRFM model was used to cluster the customers and rank them based ‎on their CLV for two groups of corporate and individual clients Clustering ‎and Discriminant Analysis techniques were implemented for this section. ‎Finally, the best strategies for bank to treat with each cluster of the ‎customers was determined.‎