Species sensitivity distributions (SSDs) remain a practical tool for the determination of safe threshold concentrations for toxicants in fresh and marine waters. While the fundamental SSD approach employed by jurisdictions around the world has remained similar over the last 20 years, variations do exist in some of the technical details of the methods and associated software tools that have been developed, sometimes leading to marked differences in results which can undermine confidence in SSD approaches. The Australian and New Zealand Guidelines for Fresh and Marine Water Quality recommend the use of the companion software tool, Burrlioz 2.0 for the derivation of guideline values. While this has proved a highly valuable tool, a range of issues have been identified over the years with Burrlioz. There is has been growing interest in the ssdtools open-source R package and associated web-based shiny app (https://bcgov-env.shinyapps.io/ssdtools/) front end as a potential alternative to Burrlioz. Here we summarise the outcomes of a joint 2.5 year collaborative research project involving Australian and Canadian researchers who undertook extensive investigations into methodologies and tools associated with SSD modelling, focusing on Burrlioz and ssdtools. While a range of topics were investigated during the project, we focus on comparisons between Burrlioz and ssdtools using collated benchmark and synthetic datasets; the development and evaluation of mixture distributions as a potential candidate for accommodating bimodal data; and an assessment of bias and coverage across a range of candidate distribution sets used in model averaging. The findings of the project have formed the basis for a suite of recommendations to the Australian-New Zealand and Canadian jurisdictions regarding the use of ssdtools and model averaging for deriving PC/HC values using SSDs.