Objective：To lay the foundation for the health sector and to provide accurate disease dynamics and early warning by con－structing a variety of prediction models of hand，foot and mouth disease（HFMD） in Chongqing and to evaluate its effect. Methods：Three kinds of single prediction models（SARIMA，BPNN and Elman neural network） and three combined prediction models（SARI－MA-BPNN，SARIMA-Elman，BPNN-Elman） were established for the monthly incidence of HFMD in Chongqing from 2009 to 2014. The models were evaluated by using the monthly incidence data of HFMD in 2015，and the optimal warning model was selected to predict the incidence of HFMD in Chongqing from 2016 to 2017. Results：The results showed that the mean absolute error（MAE），mean error rate（MPAE），prediction accuracy（P），non-linear correlation coefficient（RNL） and mean relative error（MRE） of the SARIMA model，BPNN model，Elman model，SARIMA-BPNN，SARIMA-Elman，BPNN-Elman combined model respectively were 0.595，0.515，0.485，0.551，0.493；0.265，0.229，0.771，0.673，0.029；0.234，0.202，0.798，0.737，0.142；0.248，0.215，0.785，0.714，0.101；0.328，0.284，0.716，0.620，0.103；0.229，0.198，0.802，0.745，0.071. Through comprehensive evaluation of various indicators，the optimal prediction model is BPNN-Elman combination model. The average annual incidence of HFMD of the year 2016 and the year 2017 in Chongqing were 162.8/10 million and 160.9/10 million based on BPNN-Elman combination model with 95% confidence interval of -0.236 to 0.184. Conclusion：The BPNN-Elman combined model has the best prediction effect and can better predict the incidence of HFMD in Chongqing，which provides a scientific basis for prevention and treatment of HFMD.