Multioutput support vector regression (SVR) is implemented to simultaneously predict the selectivities and the CH4 conversion against experimental conditions in methane oxidation catalysts. The predictions unveil the details of how each selectivity and CH4 conversion behaves in each catalyst. In particular, the selectivity and the CH4 conversion of Mn-Na2WO4/SiO2, Ti-Na2WO4/SiO2, Pd-Na2WO4/SiO2, and Na2WO 4/SiO2 are predicted, and the effects of Mn, Ti, and Pd are unveiled. In addition, the trade-off points of CO and C2H6 are identified for each catalyst, leading to maximization of the C2H6 yield. Thus the simultaneous prediction of the reaction trend with catalysts not only will help with the understanding of the catalyst activities but also will provide guidance for designing the experimental conditions.