The integrated-servo-actuator (ISA) is one of the most critical subsystems of aircraft flight-control system, which controls the speed, direction, displacement, and force of load for an aircraft. The degradation state of the ISA directly influences the safety of the aircraft. Hence, it is valuable to predict the degradation of the ISA to ensure its operating reliability. However, as a kind of complex system, the degradation mechanisms and the influences of the stress cannot be fully understood. Moreover, the nonlinear degradation process brings more difficulties to establish an accurate life prognosis model. To address these challenging issues, this paper proposed a hybrid degradation prognosis method that fused the physics-based model and data-driven model for ISA. The nonlinear Wiener process (NWP) algorithm is utilized to characterize the physical degradation process of ISA. The effect of different stresses is quantitatively modeled. Furthermore, the data-driven echo-state-network (ESN) is optimized to describe the nonlinear degradation process of ISA. More degradation data are generated based on the NWP model for ESN model training. Therefore, the degradation trajectory predicting model is fused with the physics-based degradation prognosis model so that both the degradation mechanisms and time series features within the monitoring data are combined. The experimental results based on the real ISA data illustrate that the proposed method has higher prediction accuracy which is meaningful to enhance the operating reliability of the ISA.