As a second criterion of uncertain decision, chance-constrained programming was introduced by Charnes and Cooper [6]. In chance-constrained programming, it is required that the objectives should be achieved with the stochastic constraints held at least α of time, where α is provided as an appropriate safety margin by the decision maker. The employment and development of chance-constrained programming in portfolio analysis with stochastic parameters can be found in [2], [7], [10], [11] and [30]. Following the idea of stochastic chance-constrained programming, Liu [17] developed a spectrum of general forms of fuzzy chance-constrained programming. To the best of the author’s knowledge, there is little research on chance-constrained portfolio selection in fuzzy environment. The author tries to do something in this area. In this paper, returns of securities were assumed to be fuzzy parameters instead of stochastic ones. The portfolio will be selected according to two types of chance criteria. By one chance criterion, the objective is to maximize the investor’s return at a given threshold confidence level. By another chance criterion, the objective is to maximize the credibility of achieving a specified return level subject to the constraints.