Temperature is one of the important characteristic parameters of civil aircraft hydraulic system performance. To effectively realize the temperature monitoring of hydraulic system, the method of Kriging model based on atomic search (ASOKM) is proposed based on Kriging model and atomic search algorithm (ASO). Firstly, the temperature fault causes of hydraulic system are analyzed, and fault logic diagram is established to clarify the characteristic parameters affecting the hydraulic system temperature. Then, combined with the quick access recorder (QAR) data, the modeling principle of ASOKM method is discussed. Finally, the effectiveness of the proposed ASOKM method is verified by the temperature monitoring analysis of domestic civil aircraft hydraulic systems. The results show that the training and monitoring average absolute errors of the ASOKM method are lower than the response surface method (RSM), Kriging, and back-propagation-artificial neural network (BP-ANN) models, and have higher accuracy, efficiency, and robustness. The proposed ASOKM method can provide a reference for reliability analysis, fault diagnosis, and predictive maintenance of the hydraulic system.