Surrogate methods (metamodels) are convenient to determine the mathematical relationship underlying the high dimensional complex systems, which are usually computationally expensive. Various stand-alone metamodels have been proposed in literature, and the ensemble of metamodels was being intensively studied recently to utilize the information reveals in construction of different metamodels. Compared with the stand-alone metamodels, the ensembled models were more robust and adaptable. The strategy of the ensemble by comparing the difference of the probability distribution of predictions was considered, where the Kullback-Leibler divergence was introduced to calculate the differences. Experiments show that the strategy has comparable accuracy in predictions with the most accurate standalone metamodel, and it can also perform better in recovering the distribution of the true response.