The design and reassessment of quays is subject to uncertainties. Examples of these uncertainties are the soil parameters, soil behavior and the current state of the structural parts. Especially in the reassessment of existing structures it is hard to prove a quay to be safe. In this thesis Bayesian updating is used as a method to reduce this uncertainty. Bayesian updating is a technique to probabilistically update the model prediction based on measurement data. One of the solutions to obtaining this data is test loading a quay wall. How to perform a test load and possible other solutions to obtaining the measurement data are not part of this research. The research focusses on how to use the data one obtains from a test loading. The effectiveness of test loading is reviewed by performing Bayesian updates with several fictitious measurement cases. Both Blum and a finite element model are updated based on fictitious strain and displacement measurements. The results show that Bayesian updating successfully reduces the standard deviations in all model predictions. This has a significant impact on the calculated reliability indices. The key benefit of performing a Bayesian update is that a statistically most likely combination of stochastic input parameters is determined. The thesis gives recommendations towards an application of Bayesian updating in practice and as fictitious measurement cases are used, an overall strategy is given for obtaining the required measurement data in practice.