A Floater module containing several empirical parameters has been added to the TNO’s Cost model in order to include the analysis of floating wind turbine support structures and mooring systems. It is of our interest to know which model parameters within the Floater module contribute most significantly to the mooring system costs and ultimately to the levelized cost of energy (LCOE). The strategy employed relies on constructing a surrogate model (based on Kriging), which is then used to perform global sensitivity analysis. For the scenarios studied here, it was found that the model parameter related to the mooring line breaking load coefficient remained the most sensitive to the capital expenditure (CapEx) cost, while the model parameter related to the failure event cost for mooring line repair remained most sensitive to the operational expenditure (OpEx) cost. Additionally, the study aimed at expanding the deterministic Cost model to systematically account for stochastic model parameter inputs in order to reduce modelling uncertainties and contribute towards more reliable mooring line designs.