Considering the uncertainty of economic conditions, multi-objective optimisation can be favoured to single-objective optimisation for process design.However, from the Pareto sets generated by multi-objective optimisation it is not obvious to identify the best one, given that each solution is optimal with regard to the selected objectives. A method taking into account the economic parameters uncertainty to support decision making based on the Pareto-optimal solutions is proposed. It uses a Monte-Carlo simulation to define the probability of each of the Pareto optimal configuration to be in the list of the best configurations from the economical point of view. For a given economic context defined the most probable best configurations are identified.The proposed method is applied to two cases: the CO 2 capture in power plants and synthetic natural gas production from biomass resources. The results allow to identify the most attractive system designs and give recommendations for the process engineers.