This thesis considers the good environmental governance of deep-seabed mining (DSM), with a focus on the seabed ‘Area’ beyond national jurisdiction (ABNJ). DSM in ABNJ has not yet begun, due in part to a lack of internationally agreed upon regulations. Shortly after this thesis research began, however, the International Seabed Authority (ISA) began consultations and drafting of its exploitation regulations, making this research particularly timely. Herein, two themes run throughout: i) transparency and ii) statistically robust monitoring of environmental impacts. For each of these themes, the research presented here suggests that there is considerable room fort he ISA to improve its practices. For example, it is currently much less transparent than bodies managing international fisheries (Chapter 2). Furthermore, its practices largely do not meet the expectations contained in recognised standards for terrestrial mining and other related sectors(Chapter 3). Regarding the monitoring of environmental impacts, the ISA calls for statistical robustness. However, it currently lacks guidance on how such robustness should be assessed and reported upon. Mortality modelling conducted here (Chapter 4), using data from the Clarion Clipperton Zone, suggests that impacts on benthic megafauna from neighbouring polymetallic nodule mining operations could be difficult to detect until it is ‘too late’; i.e. only after serious harm has already occurred. To be able to detect early warnings of possible serious environmental harm, monitoring design will need to take into account increased statistical power from the outset, which will require large sample areas (containing 500-750 individuals) and adequate replication ( ≥5 sites) in order to be able to rule out ‘false negatives’; i.e. type II errors. The thesis contains 45 recommendations, which if implemented by the ISA would improve the likelihood of statistically robust environmental monitoring and informed decision making. Additionally, in Chapter 5 (Epilogue), three simply stated, overarching good practices are put forward, not only for the ISA, but for DSM contractors and researchers alike: i) ensure DSM environmental data are readily available; ii) establish robust statistical practices in the analysis of environmental data; and iii) be inclusive when considering the results of environmental data analyses.