Under the Canadian Environmental Protection Act, 1999, Environment and Climate Change Canada and Health Canada may assess and manage risks of chemical substances to the environment and to human health. Due to the often scarce nature of available empirical information and the need to take timely actions to mitigate potential risks, several science-based approaches to address information gaps for data-poor substances may be used. These include generation of new empirical data, use of modelling tools, and application of analogues/read-across. The read-across approach is an efficient and effective approach that may be used in parallel with other lines-of-evidence in a weight-of-evidence approach to reduce uncertainties in risk assessments of data-poor substances. Chemical structure, functional application, and mode of action have been considered to identify suitable analogues for a target substance. More recently, application of the read-across approach has expanded to include not only parent substances but also their transformation products, especially for substances suspected to have their toxicity elicited through the latter. Halogenated aromatic flame retardants (FRs) have been in commerce including the Canadian market for years, and are added to manufactured materials for the purpose of slowing the ignition and spread of fire. Due to similar applications, functions, or chemical structures among subgroups of FRs within a category, many FRs are considered analogues to one another. This poster highlights the process and approaches, to identify suitable analogues for certain halogenated aromatic FRs in the Chemicals Management Plan. The approach is based on available science and comparable to guidance from other jurisdictions, and may take into consideration similarity in chemical structure, physical-chemical properties, toxicodynamics, and toxicokinetics in both parent substances and their transformation products. When science-based considerations are applied to identify suitable analogues for read-across, it is possible to reach evidence-based risk assessment conclusions, even in the absence of empirical data.