Underwater sounds caused by military sonar, seismic surveys and marine renewable construction/operational activities can harm/disturb acoustically sensitive marine mammals, and many jurisdictions require such activities to undergo environmental impact assessments to guide mitigation. The ability to assess impacts in a rigorous, quantitative way is hindered by large knowledge gaps on hearing ability, sensitivity and responses to noise. We will describe an analytical framework, called SAFESIMM (Statistical Algorithms For Estimating the Sonar Influence on Marine Megafauna) which partitions our knowledge of noise impacts into linked modules that collectively calculate the numbers of animals likely to be affected by noise. The simulation framework will be illustrated using two species that are relevant to marine renewable assessments in the UK, namely grey seal (Halichoerus grypus) and harbour porpoise (Phocoena phocoena). We have run a suite of simulations which consider sensitivity to uncertainty in three areas: how sound energy is perceived by animals with differing hearing apparatuses; how animals move in response to disturbance (i.e., the strength and directionality of evasive tactics); and the level of site fidelity effects. In particular we consider sensitivities over exposure scenarios of differing lengths. We will describe the main outcomes of these simulations and place the results in the context of the decisions that developers and regulators are faced with. Simulation frameworks offer a powerful way to explore, understand and estimate effects of cumulative sound exposure on marine mammals, but they can act as black boxes that hide important, but subjective, decisions. For example, we have found that the estimate of received sound exposure level (SEL) is influenced most strongly by the weighting function used to account for the species’ presumed hearing ability and therefore tools that make different assumptions about auditory weighting will give contradictory recommendations to managers about sound exposure relative to allowable harm limits.