Abstract Because of its well-documented subduction zone and outer island arc, Sumatra provides a unique setting for studying and forecasting earthquakes within the seismically active Sunda Arc. This study builds on previous research that utilized Global Positioning System data and the Akaike information criterion to analyze probabilistic seismic hazard functions. However, this study replaces surface displacement rate data with a forward model derived from previous fault modeling results to create a more broadly applicable earthquake forecasting algorithm. Although the best-fit model patterns generated by this new algorithm are consistent with past studies, the forward model demonstrates a lower degree of fit compared to models utilizing natural surface displacement data. This discrepancy highlights the need to refine the fault parameter models to estimate surface displacement rates. Despite this limitation, the study makes a valuable contribution by developing a general algorithm applicable to other subduction zones within the Sunda Arc region. With further refinement and incorporation of more accurate fault modeling and data, this algorithm has the potential to formulate the best-fit earthquake spatial forecast models. This approach could be applied to other seismically active areas, particularly those near subduction zones.