In this study, a numerical model (XBeach-vegetation) and statistical Bayesian Network (Netica) was developed for the simulation and quantification of wave attenuation for various combinations of global salt marsh characteristics and extreme hydraulic conditions. The purpose of this modeling effort was to test the ability of the numerical model and statistical model in properly simulating salt marsh-hydraulic interactions which occur around the world. Additionally, testing of the ability of this model to quantify wave attenuation over salt marsh habitats while under extreme hydraulic conditions (high wave heights and water levels) was performed. First, the numerical model was calibrated, tested, and validated based on both a field and flume study which measured wave attenuation over natural salt marsh. Next, the numerical model was used to produce many results for wave heights at various locations over a salt marsh platform. These results produced a dataset which was input into a Bayesian Network (BN) for further organization and quantification of wave attenuation by global salt marshes. Finally, the salt marsh components were tested for their influence on the BN, and the results were compared to the Xbeach-vegetation results for several cases in order to provide an example of how each method produces results. Initially, the numerical model was calibrated and validated based on wave data which was provided by members of the BE SAFE study and was recorded during a winter storm in 2015 at Hellegat Polder, Western Scheldt, the Netherlands. The numerical model simulated the recorded wave heights accurately, and proved to be effective in reproducing results for extreme hydraulic conditions recorded at Hellegat. Additionally, the numerical model was tested on the conditions of the Hannover wave flume study, which generated extreme waves in one of the largest wave flumes around the world, in order to measure wave attenuation by a 40 meter section of natural salt marsh at the end of the flume. Once the model was calibrated and validated, the set-up for a batch of numerical model simulations took place. In order to assign inputs which were representative of global coastal salt marsh habitats, data was collected from many sources to form a database. Next, the numerical model was set-up in order to simulate waves occurring over an arbitrary salt marsh platform for many different salt marsh characteristics and hydraulic conditions. Wave heights were obtained at five distances across the salt marsh platform, and the results were input into a BN for further data handling. The BN (Netica) was used to structure and organize the data into a compiled network, which was completed before the network could be used further. Once the network was compiled, the various salt marsh characteristics and hydraulic conditions were varied within the network in order to see which characteristics and conditions were most likely to produce certain wave heights at various distances throughout the salt marsh platform. The influence of each characteristic and parameter could additionally be quantified in a probabilistic manner using the network. In selecting the various values within each node of the BN separately, an assessment could be performed in order to see the influence of each salt marsh component on the resulting wave heights. The results produced by both the Netica program and the Xbeach-vegetation model were presented in order to show a comparison of how each method presents the results. Finally, a sensitivity analysis of the various salt marsh characteristics was performed to obtain knowledge on how these components influenced resulting wave heights. Once all of this was completed, conclusions were made based on the results, and recommendations were provided for the improvement of future research efforts within this field.