As more innovative organic Rankine cycle (ORC) designs are being proposed, it is becoming more important that a reliable and robust modelling approach is crucial for optimizing these systems. While commercial simulation software exists, most are not tailored for optimization and they generally cannot guarantee global optimum. This paper proposes a modelling approach to approximate a rigorous simulation model that is suitable for global optimization. This involves a combination of regression and thermodynamic analysis, in addition to integer programming techniques. Three different global solvers, namely MATLAB’s genetic algorithm solver (ga), SCIP, and BARON are used to optimize the ORC model and are compared against each other to demonstrate the prospect of achieving the global optimum using this approach. In addition, this paper also presents a technique to improve the model accuracy and computation time by using a piecewise fit to approximate the output characteristic of the ORC unit operations.