In recent years, the research on risk measurement and control methods based on big data analysis model has become more and more important, and the backtesting analysis on risk measurement tools can guarantee the effectiveness of the techniques used in actual data analysis. Marginal Expected Shortfall(MES) is an important tool to measure the marginal contribution of individual institutions to systemic risk, and the backtest methodologies for MES is also worthy to focus on. In this paper, the backtest method of ES in C. Acerb et al. is extended to the two-dimensional case and two backtest methodologies are proposed for MES. The results of simulation show that these two new statistics are more powerful than the statistics used in D. Banulescu et al. under situations that the difference between the null hypothesis and the alternative hypothesis is relatively small. The results of empirical analysis also support that these two new statistics proposed in this paper accept the null hypothesis more cautiously under the same prediction model. This method can give some reference for model algorithm backtesing under big data.