The objective of this paper is to show the usefulness of multivariate statistical techniques to structure and visualize the information contained in multi-criteria matrixes obtained from the evaluation of control strategies in wastewater treatment plants (WWTP). The performance of sixteen different control strategies is evaluated by measuring their degree of satisfaction for twenty-four environmental, technical, economical and legal objectives using the “Neptune Simulation Benchmark” (an A2O WWTP removing organic matter, nitrogen and phosphorus). Cluster analysis (CA), principal component /factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the simulation output of the tested control strategies. The results of the case study show that multivariate analysis is a useful tool to straightforwardly differentiate WWTP control strategies with multiple criteria. Specifically, CA identified similar patterns in the alternatives with and without external chemical addition and/or TSS controller. Also, PCA/FA allowed discovering the main correlations between the evaluation criteria and the control strategies influencing those criteria most. Finally, thanks to DA it can be seen that from the original list of evaluation criteria, only a small sub-set of four, i.e. sludge production, aeration energy and time in violation of effluent limits for COD and P, cause the main differences in the overall process performance. Future evaluation of control strategy performance can therefore be restricted to an evaluation of only these four criteria.