This article presents a study of the effect of process uncertainty on the optimal design of a CO2 capture pilot-scale plant for coal-based power plants. The presented Work employed a novel method in the Optimal design of large-scale chemical processes (such as the CO2-capture plant) under uncertainty, which uses a power series expansion (PSE) approximation to the actual nonlinear process in computing the output distribution of the process constraints due to uncertainty. A ranking-based approach is employed here where priorities Or probabilities of satisfaction are assigned to the process constraints considered in the analysis. In this work, uncertainty is assumed in three input variables affecting the operation of a CO2-capture pilot plant, namely, the CO2 content and the temperature and flow rate of the flue gas stream. The design of the optimal plant aims to specify the sizes of the key process units included in the CO2-capture pilot plant, such as the packed column height and diameters and heat exchanger and condenser areas, that minimize the process economics in the presence of uncertainty in the flue-gas stream conditions. The results of the study using the proposed method show that, to ensure a desired target CO2 removal rate in the presence of process uncertainties in the flue gas stream, larger designs for both the absorber and stripper towers and a higher reboiler heat duty are required. Although the present method yields larger and, thus, more expensive designs, it ensures that the environmental and operating constraints are satisfied according to the user-defined probability of satisfaction, whereas the original pilot-plant base-case design violates the target for the CO2 removal rate most of the time when operating under uncertainty.