In order to predict the chemical oxygen demand(COD) removal rate of the diazodinitrophenol(DDNP) wastewater treated by supercritical water oxidation(SCWO)，the HXDK-01-A intermittence type supercritical water oxidation device was used to dispose the actual industrial production wastewater，and the effects of reaction temperature，reaction pressure，residence time，oxygen excess on COD removal rate were studied. A single hidden layer Elman prediction model was established by using the reaction temperature，reaction pressure，residence time，oxygen excess as input variables，and using the COD removal rate as output. The MSE of the Elman model is 0.0418，the biggest error is -0.3231，and the least error is 0.0296，the MSE of the multiple regression is 0.3149，the biggest error is 0.8830，and the least error is 0.2200. The Elman neural network prediction results are better than that of multiple regression analysis. Results show that the Elman model can be adopted to predict the COD removal rate of the wastewater treated by SCWO.