<p>This study investigates how heterogeneity in lifestyle and physical fitness shapes patterns of brain ageing in depression. The study sample included medically healthy adults from the UK Biobank (44–82 years) with a history of depression (<i>n</i> = 896) and non-psychiatric controls (<i>n</i> = 36,206). Heterogeneity through Discriminative Analysis (HYDRA) was used to derive data-driven subgroups within the depression sample based on 224 behavioural and physical health features. Global and voxel-based brain-age-gap-estimates (brainAGE) computed from structural neuroimaging data were used for personalized assessment of brain ageing. Four depression clusters were identified: the “balanced-active” cluster (<i>n</i> = 253) characterized by an active lifestyle and balanced diet; the “low metabolic risk-active” cluster (<i>n</i> = 178) characterized by a health-conscious dietary and exercise lifestyle; the “high metabolic risk-sedentary” cluster (<i>n</i> = 315) who had higher body mass, poor diet, and sedentary behaviour; and the “frailty-moderately active” cluster (<i>n</i> = 150) who had a varied diet but coupled with physical frailty. Mood symptoms were lowest in the “balanced-active” cluster and highest in the “high metabolic risk-sedentary” cluster. While depression overall was associated with minimally accelerated global and local brain ageing in fronto-limbic regions, the “high metabolic risk-sedentary” cluster showed additional, regionally specific acceleration in prefrontal, parahippocampal, and thalamic areas. This work underscores the importance of lifestyle and fitness heterogeneity when examining associations between depression and neurobiological ageing and supports lifestyle-informed stratification as a pathway toward more targeted intervention strategies.</p>