A processor-implemented method for determining an optimum multi-column chromatography MCC configuration of an MCC process, the method comprising the steps of: receiving, via one or more hardware processors, feed characteristics, targets for some of one or more key performance measures of the MCC process, one or more MCC configurations of the MCC process, one or more column characteristics of each column of one or more columns present in each MCC configuration, and media characteristics of one or more chromatography media for use in each column of one or more columns; selecting, via the one or more hardware processors, a chromatography column CC process model set from a plurality of CC process model sets, based on the media characteristics of the one or more chromatography media for use in each column of the one or more columns and one or more components present in the feed and included in the feed characteristics, wherein each CC process model set comprises (i) a mobile phase mass transfer model and associated mobile phase model parameter (ii) a stationary phase mass transfer model and associated stationary phase parameters, and (iii) an adsorption-desorption model and associated adsorption-desorption parameters; determining through an optimization technique, via the one or more hardware processors, values of one or more decision variables that optimizes the one or more key performance measures of the MCC process using said targets, to obtain optimized values of the one or more key performance measures, for each MCC configuration of the one or more MCC configurations, using the selected CC process model set, wherein the one or more decision variables are associated with operating conditions to be maintained at each chromatographic operation of a set of chromatographic operations to be performed at each stage, and the one or more column characteristics of each column of one or more columns present in the MCC configuration; and determining, via the one or more hardware processors, the optimum MCC configuration out of one or more MCC configurations, based on the associated optimized values of the one or more key performance measures of the MCC process. receiving, via one or more hardware processors, feed characteristics, targets for some of one or more key performance measures of the MCC process, one or more MCC configurations of the MCC process, one or more column characteristics of each column of one or more columns present in each MCC configuration, and media characteristics of one or more chromatography media for use in each column of one or more columns; selecting, via the one or more hardware processors, a chromatography column CC process model set from a plurality of CC process model sets, based on the media characteristics of the one or more chromatography media for use in each column of the one or more columns and one or more components present in the feed and included in the feed characteristics, wherein each CC process model set comprises (i) a mobile phase mass transfer model and associated mobile phase model parameter (ii) a stationary phase mass transfer model and associated stationary phase parameters, and (iii) an adsorption-desorption model and associated adsorption-desorption parameters; determining through an optimization technique, via the one or more hardware processors, values of one or more decision variables that optimizes the one or more key performance measures of the MCC process using said targets, to obtain optimized values of the one or more key performance measures, for each MCC configuration of the one or more MCC configurations, using the selected CC process model set, wherein the one or more decision variables are associated with operating conditions to be maintained at each chromatographic operation of a set of chromatographic operations to be performed at each stage, and the one or more column characteristics of each column of one or more columns present in the MCC configuration; and determining, via the one or more hardware processors, the optimum MCC configuration out of one or more MCC configurations, based on the associated optimized values of the one or more key performance measures of the MCC process.