This work presents an experimental design methodology combined with computational simulation to correlate the influence of operational conditions and reactants charge in the numeric average molecular weight (MWN) as well as on monomer conversion (X-CL), for the hydrolytic polymerization of nylon-6 in a semibatch reactor. It evaluated the reaction temperature, the pressure profile, and the proportion of reactants in the charge. Experimental design was used to screen the most statistically significant variables and to develop a reliable predictive model for each response. The combined use of the models can be applied for process optimization, by establishing MWN and maximum X-CL as objective functions. Responses surface allowed the visualization of the responses behavior when changing the independent variables and therefore to identify the optimal tendencies. This work demonstrates that such methodology can be applied for optimization of complex processes like the hydrolytic polymerization of nylon-6. This polymerization has many side reactions occurring at the same time, which are sensitive to different profiles of pressure and temperature that are applied. This evaluation is quite interesting as such profiles are necessary to perform the several polymerization steps and have a significant impact on product characteristics and therefore in its applications. (C) 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 127: 2910-2921, 2013