As a result of growth in the offshore energy infrastructure, the connection between the offshore environment and the mainland is increasing in importance. This leads to an increased use of the seabed for cables and pipelines as part of our energy infrastructure. Cables or pipelines are placed in trenches and covered by sediment, to be protected from any damage from activity near the sea bed. During execution, the trenches will refill with sediment prior to the placement of the cable or pipeline, which is known as siltation. The siltation rates are increasing when entering the breaker zone near the shoreline. The predictability of the siltation rates are a crucial step in efficient and safe realisation of new connections between the offshore energy infrastructure and the mainland. Inclusion of nearshore processes is missing in existing quick-assessment siltation tools. Complex process-based models, like Delft3D or XBeach, are capable of predicting siltation volumes in the nearshore environment accurately. However, these models demand large computation capacities. This makes them unsuitable for probabilistic modelling, requiring large numbers of calculations. Probabilistic modelling however is a crucial step in identifying and quantifying uncertainties and related risks in the execution. This research presents a quick-assessment tool that includes nearshore processes. Ensuring low complexity makes quick-assessment tools suitable for probabilistic modelling of siltation predictions, reducing and quantifying uncertainties within nearshore trench siltation. This research presents an approach to include wave transformation and wave-driven currents into an existing siltation prediction tool (SedPit). The resulting SedPit Nearshore tool allows fast predictions of siltation volumes in the nearshore zone. The performance of the SedPit Nearshore tool is assessed by comparing it to data from a field case, and comparing the accuracy to the accuracy of the existing SedPit tool. The SedPit Nearshore tool gives accurate predictions on the total siltation volume, and gives good insights in the spatial distribution of siltation volumes. The potential of the SedPit Nearshore becomes most evident when comparing it to the existing SedPit tool. A great improvement compared to the existing SedPit tool is seen. For the test case, the SedPit Nearshore tool reduces the absolute error in redicting the total siltation volumes by 82% compared to the existing SedPit tool. The SedPit Nearshore tool predicts the total siltation volume with an error margin of 7%, while the existing SedPit has an error margin of 41%. The largest improvements compared to the existing Sedpit are seen in the most onshore regions, as this is the zone where most wave-driven currents are generated. The computational speed of the tool has proven its applicability for analyses on model sensitivity and uncertainty quantification. Computation times are reduced by factor 9,000 when comparing it to XBeach, a complex process-based model. Bottom roughness ks and wave roller steepness β were identified as most influential free variables in driving nearshore siltation volumes. Calibrating the model to obtain likely values for a range of free variables has helped to reduce the 95% confidence interval of peak siltation rates by 36%. The inclusion of wave-driven currents into existing siltation prediction tools has shown a great improvement in the accuracy of siltation predictions in the nearshore zone. Although the SedPit Nearshore tool is calibrated on one specific field case, the method and the workflow of the tool show potential to help as general prediction tool of nearshore trench siltation. The power of the SedPit Nearshore tool lays in its simplicity, making it a fast, efficient, and accurate tool, suited for probabilistic modelling.