Individual Pension System (IPS) is a personal future investment system that allows individuals to regularly save for their retirement.IPS is enacted by the law and supported by the government through state contribution. In Turkey, IPS entered into force on October 27,2003 and it achieved an impressive progress over the last years. This improvement has caused increase in amount of raw data stored indatabases. However, accumulated data are complicated and big to be processed and cannot be analyzed by classical methods. Datamining is becoming an essential tool to discover hidden and potentially useful knowledge from raw data. For this reason, application ofdata mining techniques on Individual Pension Savings and Investment system is necessary. In this study, one of the data miningtechniques, decision tree classification, was used to determine customers’ profile. SPSS Clementine 12.0 software was used to developa classification model. Analyses were performed by various decision tree algorithms. Some customer information of a pensioncompany operating in Turkey were extracted from system. The significant rules about customers were revealed by analysis. The resultsof analysis indicated that the CHAID algorithm showed the best prediction with an accuracy of 85.64% among C5.0, C&R Tree, QUEST.