Abstract People age differently. Differences in ageing might be reflected by metabolites, also known as metabolomic ageing. Predicting metabolomic ageing is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic ageing is unknown. We studied exposome-related exposures as potential predictors of metabolomic ageing, both cross-sectionally and longitudinally in men and women. We used data from 4459 participants, aged 36-75 of round 4 (2003-2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at round 4. Longitudinal exposures were based on the average exposure over 15 years (round 1 (1987-1991) to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R 2 6.8 and 5.8 respectively) and women (R 2 14.8 and 14.4 respectively). Biological and diet exposures were most predictive for metabolomic ageing in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic ageing in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic ageing were from the biological and lifestyle domain and differed slightly between men and women.