As populations expand in the coastal zone and climate change increases the risk of coastal flooding and erosion hazards, there is a growing need to understand how coastal dunes will evolve into the future. In recent decades, the development and extension of numerical models for dune evolution have demonstrated capabilities to successfully replicate ecomorphodynamic interactions at various spatial or temporal scales. Here, we compare the ability of two numerical models, the analytical Dune Response Tool (DRT) [1] and the process-based AeoLiS model [2], to replicate historical dune growth along a rapidly prograding section of coast in Long Beach, WA. After calibrating coefficients in the erosion and accretion modules of the analytical model, the DRT accurately reproduced historical dune evolution using minimal computational resources. AeoLiS was also able to reproduce patterns in dune growth when detailed field observations and a shoreline change rate module were added to the model. The final DRT profile does not perfectly mimic detailed topographic patterns observed in the field, but it has a lower RMSE than results from AeoLiS. Moreover, DRT’s efficiency and minimal calibration requirements make it an easily implementable tool. In contrast, AeoLiS requires extensive field observations as inputs for accurate hindcasts, but the final result better matches the observed complex dune evolution. Both the DRT and AeoLiS models have the potential to offer valuable insight into predicted dune evolution and the coastal protective services dunes may provide in the future.