Abstract: To deal with the problem of high cost and low accuracy existing in conventional methods for the blending process in lead-zinc sintering, a kind of methodology for intelligent integrated modeling and synthetic optimization is proposed in this paper. First, based on the process neural network model and improved grey system prediction model, an intelligent integrated model is presented using the concept of entropy to not only guarantee the composition prediction precision of Pb-Zn agglomerate but also meet the requirements of the data completeness by blending computation. Then, a blending optimization model is established for the purpose of minimizing the costs. Finally, the mixture ratios are optimized by using a qualitative and quantitative meta-synthesis methodology based on the expert reasoning strategies and improved immune genetic algorithm. The simulation results demonstrate the validity of the proposed methodology.