Criteria/correlations proposed in the literature to predict the performance of an adsorbent in a separation process fail in three ways for carbon dioxide (CO2) capture and concentration (CCC) from flue gas: (i) they cannot confirm if the stringent purity-recovery requirements will be met, (ii) the indices rank the adsorbents for a fixed set of operating conditions and not for the best performance for each adsorbent while satisfying the purity-recovery constraints, and (iii) the performance indicator for which the adsorbents are ranked is not explicitly stated, and certainly one index cannot apply for different performance indicators. In this study, a two-step method has been developed for rapid screening of the adsorbents for postcombustion CCC as a function of five easily quantifiable equilibrium isotherm characteristics of the CO2 isotherm, namely, its binary mixture selectivity over N-2, equilibrium loading, local slope and nonlinearity at the feed concentration, and Henrys constant. First, a study has been conducted using a central composite design of experiments for determining the effects of these isotherm characteristics. The performance of a four-step vacuum swing adsorption (VSA) process with light product pressurization has been optimized for each combination of the aforementioned CO2 isotherm characteristics, representing a possible adsorbent, with the objective to minimize energy consumption and maximize productivity while satisfying the purity-recovery constraints. Among the feasible combinations of isotherm characteristics, some were unable to meet the purity-recovery constraints. Next, a neural-network-based model has been proposed to predict whether an adsorbent can deliver CO2 at 95% purity and 90% recovery. Finally, for adsorbents that pass this first test, meta-models have been developed to predict the minimum energy consumption and maximum productivity of the process. The proposed screening method has been validated with a large number of adsorbents considered in recent published studies. In the process, we have identified several adsorbents that promise a much superior performance over that of 13X zeolite, the most studied adsorbent for postcombustion CCC.