Preference Selection Index (PSI) that is a Multi-Criteria Decision Making Method (MCDM) does not need to determine the weights for criteria and it has been applied in many different fields. However, using only the data normalization method (DNM) proposed by the inventor of the PSI method may narrow the application scope of this method. This study aims to expand the application range of the PSI method by identifying the appropriate DNMs in combination with the PSI method. Twelve different DNMs were used in combination with the PSI method. These twelve combinations were used in turn to solve several problems in different fields. The ranked results of solutions by these combinations were all compared with the results in the published studies. The sensitivity analysis of the ranked results of the solutions in each case also was performed. In this study, four out of twelve DNMs were found to be appropriate in combination with the PSI method. This discovery has extended the application scope of the PSI method that the previous methods have not met.