In the design of a chemical process (CP), certain design specifications (for example, those related to process economics, process performance, safety, and the environment) must be satisfied. During the operation of the plant, because design models have uncertainties associated with them, we need to ensure that, within the region of uncertainty, all design specifications are satisfied. In recent years, research has focused on the investigation of the process flexibility (Biegler et al. Systematic Methods of Chemical Process Design; Prentice Hall: Englewood Cliffs, NJ, 1997) based on the feasibility function (Halemane and Grossmann AIChE J. 1983, 29 (3), 425) which is a measure of the CP's ability to meet design specifications under uncertainty. Several researchers have proposed methods for calculating the process feasibility function, which involves solving a very complex multiextremal and nondifferentiable optimization problem. Current methods for calculation of the flexibility function use an enumeration procedure (explicit or implicit), which in the worst case can require a large number of iterations. To try to address this issue, in this paper, we have introduced an efficient approach, which avoids enumeration. Through examples, we have shown that the new method leads to a small number of iterations and has low CPU requirements.