Heat exchanger networks (HENS) discharge a large amount of low-grade heat to the cold utilities, resulting in excessive energy consumption. Organic Rankine cycle (ORC) which converts low-grade heat into electricity is a promising technology to recover such low-grade heat. The operating parameters of ORCs are determined according to the amount and quality of the low-grade heat generated from the HEN. Therefore, it is necessary to optimize the ORC and the HEN simultaneously, which is the goal of this work. The proposed model adds the ORC streams of uncertain temperature and pressure into the stage- wise superstructure of the HEN. The thermodynamic behavior of the ORC streams is predicted by polynomial regression instead of the highly nonlinear Peng-Robinson equation of state. Both single basic ORC and dual independent basic ORCs are considered in the model. As a result, solving the proposed model could obtain ORC parameters, including the evaporation temperature, condensation temperature, and flow rate of working fluids, and HEN parameters involving the matches of process-to-process and process-to-ORC simultaneously. Case studies prove that the simultaneous method performs better than the sequential method, and superior results have been obtained compared to those in the literature.