Fuzzy approaches are used for modelling uncertainty and vagueness present in real world systems. The performance of a fuzzy system is catalyzed by the system-design. Fuzzy sets generalize classical crisp sets by incorporating concepts of membership for a fuzzy variable. Each fuzzy set is associated with linguistic concepts that are germane to a particular application. This paper presents an approach for evaluating the region of certainty and uncertainty represented in design of fuzzy linguistic variables. Fuzzy Resembler (FuzR) attempts to capture the goodness of a fuzzy system design using a geometric approach. This can be used as a filter-based analyzer for evaluating the design of fuzzy membership space. From the results it can be inferred that FuzR presents meaningful observations of a fuzzy variable, characterized by different membership functions such as Triangular, Trapezoidal and Gaussian. FuzR can be used as a design evaluation parameter for evolving fuzzy systems. Knowledge engineers can use it to optimize design of Fuzzy systems in the absence of domain experts. Moreover, the level of abstraction provided by FuzR makes it an abstract and an intuitive design parameter.