This paper presents a new approach for fuzzy classification in the hesitant environments -FCHE- by decision making process. Our intention of the hesitant environments is situations, which there are different evaluations of experts for one problem. In this paper , we focus on cases that a classifier can be designed by knowledge of experts while each expert can classify data with a feature, independently, by linguistic terms. In this paper, we assume the classification task as a decision making problem in which, each feature as an attribute, each class as an alternative and each expert as a decision maker are considered. In the new classifier , we can use different score functions and aggregation operators in hesitant fuzzy sets for fuzzy classification in various viewpoints . Finally , our new approach is applied to a practical problem in economics , then for validation of the proposed model, we use iris data from the UCI repository.

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