In recent years, Predictive Digital Twins (PDT) have emerged as a potential tool to monitor and predict the behavior of dynamic systems, including nature-based solutions in natural coastal systems. Here, we test the potential of using a simple, coupled shoreline and beach-dune model as a base for a PDT. The models exchange sediment flux balance information at each time step and recalculate shoreline positions and beach-dune profiles accordingly. We test the concept in two cases: a schematized shoreline and a case study in an existing hybrid dune-dike system. Results show that the model is sufficiently robust for consideration as a basis for the PDT. Expected alongshore patterns, such as increased dune growth for larger beach widths, emerged in the schematized test, whereas most of the trends found in the real case could also be simulated. The information exchange of sediment fluxes across beach compartments allows different models to operate at different timescales simultaneously. Parametrizations of specific sediment fluxes between beach-dune compartments may be done directly, considering sufficient information and a proper description of the process already exists. Further steps include the development of a more robust framework for model and data integration and the inclusion of different existing or new coastal models.