In the color management system, the color prediction performance of the forward color conversion model directly affects the color separation accuracy of the reverse model. Aiming at the research and development of color management system, this paper aims to study and analyze the several influencing factors on the color prediction performance of forward Neugebauer model, and provides parameter optimization scheme for the application of the model. With the help of MATLAB platform, the cellular Neugebauer models based on different cell-levels, different locations and quantities of test samples, and the different cellular correction schemes were simulated. Through the printing and measurement experiments of samples, the influence of above factors on the color prediction performance of the cellular Neugebauer model was evaluated, and then the optimal parameter scheme of the model was determined. The result of the experiment indicated that accuracy of the model increased with the increase of cell level, but no longer with significant changes at cell-level 4 or 5. In addition, the number and location of sampling points within the cell as well as the cellular correction scheme exerted no effective influence on the accuracy of color conversion. Based on the above analysis, this paper determined to use the five-levels cellular division, the cell-center sampling and the unified cellular correction scheme (all the cells share one correction index) to optimize the cellular Neugebauer model. Compared with the same type of algorithm model, and in the case of the same number of test samples, the predicted color difference of the cellular Neugebauer model with optimized parameters, i1 Profiler software and the cellular neural network model were all less than 1 CIEDE2000 color difference unit, and the difference among them was all less than 0.15, which was within the range of system error, and the predicted color difference of the distance-weighted interpolation algorithm reached more than 3. Considering the algorithm structure, the neural network model requires training and modeling of all cells, with a large amount of computation. Therefore, considering the accuracy and efficiency of the algorithm, the cellular Neugebauer model with optimized parameters can meet the demands of color reproduction in the current printing industry.