In this paper, we focus on a complex management issue, namely the physical effects of a large-scale offshore sand extraction. For these kinds of issues there is no obvious morphological model available to answer all management questions. Therefore, we aim to answer as many management questions as possible, using a set of existing morphological models parallel to each other. In this way, we can support governments to assess applications for licenses for large-scale sand extraction. We investigate whether this parallel modeling approach is significantly more helpful in addressing the management questions than a single modeling approach. The management questions are translated into quantifiable variables, known as Coastal State Indicators (CSIs). We focus on three coastal user functions: coastal safety and maintenance, offshore infrastructure, and navigation. The selected morphological models are assessed on (1) their applicability to the CSIs and (2) the reliability of their predictions. We quantify the predictive power of the models based on these two parameters. We conclude that by using a parallel modeling approach it is possible to address more management questions effectively in comparison with using just the best single model. The use of this parallel modeling approach increases the predictive power significantly, here 35%.