Surface compositions play a predominant role in the efficiency and lifetime of membranes and catalysts. The surface composition can change during operation due to segregation, thus controlling and predicting the surface composition is essential. Computational modelling can aid in predicting alloy stability, along with designing surface alloys and near-surface alloys that can outperform existing materials. In this work, a computational model to predict surface segregation in ternary alloys is developed. The model, based on Miedema's semi-empirical model and Monte Carlo simulations, enables to predict long- and short-range ordering in the surface and subsurface layers. It is used to screen a vast range of alloy compositions to design a novel ternary Pd-based material for H₂ separation membranes. The addition of specific amounts of Cu and Zr to Pd is expected to reduce poisoning and enhance the permeability as compared to pure Pd.