In order to improve the dynamic decision level during the quality function deployment and effectivelypredict the importance of customer requirements, a forecast model based on the least square support vector machine(LS-SVM) is constructed. Then, by using the model parameters as the antibody and the importance forecast devia-tion as the antigen, the parameters of LS-SVM model are optimized by means of the clonal selection algorithm. Fi-nally, a numerical printing and die-cutting machinery of corrugated board is used as an example to verify the feasi-bility of the proposed method, and the results are compared with those obtained by the methods based on grey modeland neural network. It is found that the proposed method based on artificial immunity and LS-SVM is feasible andeffective in forecasting the importance of customer requirements.