Fuzzy logic is based on the theory of fuzzy sets, where an object’s membership of a set is gradual rather than just member or not a member. Fuzzy logic uses the whole interval of real numbers between zero (False) and one (True) to develop a logic as a basis for rules of inference. Particularly the fuzzified version of the modus ponens rule of inference enables computers to make decisions using fuzzy reasoning rather than exact. We study decision making problem under uncertainty. we analyze Max-Min method and Minimization of regret method originally developed by Savage and further developed by Yager. We generalize The MMR method by creating the parameterized family of minimum regret methods by using the ordered weighted averaging OWA operators.