Generally, chemical processes are designed with the use of inaccurate mathematical models. Therefore, it is important to create a chemical process that guarantees the satisfaction of all design specifications either exactly or with some probability. This paper considers the issue of chemical process optimization when at the operation stage the design specifications should be met with some probability and the control variables can be changed. We have developed a common approach for solving one-stage and two-stage optimization problems with joint chance constraints for the cases in which the uncertain parameters are either independent random variables with arbitrary probability distributions or dependent normally distributed random variables. This approach is based on approximate transformation of chance constraints into deterministic constraints. This excludes the numerical calculation of multiple integrals for computation of the left-hand sides of chance constraints.