In this paper, a technique to estimate fuzzy membership functions for pattern recognition purposes is proposed. The method is based on some interesting conclusions drawn in the bijective transformation between possibility theory and classical probability. A rational function approximation to probability density function is obtained from the finite histogram. The parameters representing the rational function are used for classification of the patterns. An example, utilizing this concept with a max-min decision making scheme, is given with some interesting results.