Noise pollution threatens marine ecosystems, where animals rely heavily on sound for navigation and communication. The largest source of underwater noise from human activity is shipping, and propeller-induced cavitation is the dominant source of noise from ships. Mitigation strategies require accurate methods for predicting cavitation-induced noise, which remains challenging. The present thesis explores prediction and modelling strategies for cavitation-induced noise from marine propellers, and provides insight into models that can be used both during propeller design and to generate intelligent vessel control strategies. I examined three distinct approaches to predicting cavitation-induced noise, each of which is discussed in one of the three main chapters of this thesis: a high-fidelity computational fluid dynamics scheme, a parametric mapping procedure, and the use of field measurements. Each of these three chapters presents different insight into the acoustic behaviour of cavitating marine propellers, as well both real and potential strategies for mitigating this critical environmental emission. A combined experimental and numerical study of noise from a cavitating propeller, focused on both the fundamental importance of experimental findings and the effectiveness of the numerical modelling strategy used, is detailed in the first main chapter of this thesis. The experimental results highlighted that loud cavitation noise is not necessarily associated with high-power or high-speed propeller operation, affirming the need for intelligent vessel operation strategies to mitigate underwater noise pollution. Comparison of the experimental measurements and simulations revealed that the simulation strategy resulted in an over-prediction of sound levels from cavitation. Analysis of the numerical results and experiments strongly suggested that the cavitation model implemented in the simulations, a model commonly used for marine propeller simulations, was responsible for the over-prediction of sound levels. Ships are powered primarily by combustion engines, for which it is possible to generate "maps" relating the emission of pollutants to the engine’s speed and torque; the second main chapter of this thesis presents the methodology I developed for generating similar "maps" relating the level of cavitation-induced noise to the speed and torque of a ship's propeller. A proof-of-concept of the method that used the model propeller from the first main chapter is presented. To generate the maps, I used a low-order simulation technique to predict the cavitation induced by the propeller at a range of different speed and torque combinations. A pair of semi-empirical models found in the literature were combined to provide the framework for predicting noise based on cavitation patterns. The proof-of-concept map shows a clear optimal operating regime for the propeller. The final main chapter of this thesis presents an analysis of field noise measurements of coastal ferries in commercial operation, the data for which were provided by an industrial partner. The key finding was the identification of cavitation regime changes with variation in vessel speed by their acoustic signatures. The results provide a basis for remotely determining which vessels produce less noise pollution when subject to speed limits, which have been implement in critical marine habitats, and which vessels produce less noise at a specific optimum speed. / Graduate