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Recommender System gives suggestions based on the user’s preferences and features of items. Ultimately its performance and efficiency depends on these factors and their representations. It also reduces the uncertainties by displaying item features. Here fuzzy logic in the recommendation system plays vital role to handle uncertainty. Fuzzy logic helps the user to provide most proper information related to the model. The multiple opinions from the user are taken on the basis of Voters database to take appropriate decision. In the proposed system classification of the database is done with the help of rules of decision tree and PART in which all the attributes are included whichever given. Comparison between these proves that PART works more efficiently than that of rules of decision tree. Keywords: Recommendation system for voters, Rules of decision tree, PART