AMONG VARIOUS STATISTICAL AND DATA MINING DISCRIMINANT ANALYSIS PROPOSED SO FAR FOR GROUP CLASSIFICATION, linear programming DISCRIMINANT ANALYSIS HAVE RECENTLY ATTRACTED THE RESEARCHERS’ INTEREST. THIS STUDY INTRODUCES fuzzy MULTI-GROUP DISCRIMINANT linear programming ( fuzzy MDLP) FOR CLASSIFICATION PROBLEMS. MDLP IS LESS COMPLEX COMPARED TO OTHER METHODS AND DOES NOT SUFFER FROM LOCAL OPTIMA, AND fuzzy MDLP OVERCOMES THE UNCERTAINTY INHERENTLY EXISTS DURING COLLECTING DATA. THE MODEL DETERMINES fuzzy BOUNDARIES FOR THE GROUPS AND FINDS fuzzy MEMBERSHIP GRADES FOR THE CUSTOMERS, WHICH OUTPERFORMS THE CONVENTIONAL CLASSIFICATION METHODS.