In this paper a new subjective clustering method using fuzzy inference is proposed. Changing some parameters interactively, a user can reflect his/her knowledge or intuition for the clustering. The proposed method takes account of both (1) connectivity of data and (2) linearity of the data distribution. In addition, it represents shape of cluster by a membership function and uses fuzzy reasoning to reflect subjectivity of a user effectively. The proposed method is also effective not only for clustering but also for various purposes such as data analysis, assumption test, modeling, concept formation support systems, etc. The validity of the proposed method is confirmed by computer simulation.