To solve the problems of energy shortage and waste accumulation, the method of co‐combustion of sewage sludge (SS) and peanut shells (PS) was proposed. SS‐PS co‐combustion characteristics in air were investigated using artificial neural networks (ANN) and thermogravimetric analyses (TGA). The proportion of PS in the mixture was 10%‐50%. The temperature range of PS combustion (160‐560°C) is lower than that of PS combustion (170‐600°C). Activation energy was estimated from two non‐isothermal kinetic analysis methods: Kissinger‐Akahira‐Sunose (KAS) and Flynn‐Wall‐Ozawa (FWO). The kinetic mechanism of the combustion process was determined by using the master‐plots method. Multiple ANN models were established to predict TG data of SS‐PS co‐combustion. The best prediction model (ANN21) was obtained. The results showed a good overlap between the predicted and experimental TG data. The ANN model and the master‐plots method are the main innovations of this study. This study can promote the utilization and reduction of solid waste, and give guidance for the large‐scale application of SS‐PS co‐combustion.