Spring phenology is a key indicator of temperate and boreal ecosystems' response to climate change. To date, most phenological studies have analyzed the mean date of budburst in tree populations while overlooking the large variability of budburst among individual trees. The consequences of neglecting the within-population variability (WPV) of budburst when projecting the dynamics of tree communities are unknown. Here, we develop the first model designed to simulate the WPV of budburst in tree populations. We calibrated and evaluated the model on 48 442 budburst observations collected between 2000 and 2022 in three major temperate deciduous trees, namely, hornbeam (Carpinus betulus), oak (Quercus petraea) and chestnut (Castanea sativa). The WPV model received support for all three species, with a root mean square error of 5.7 ± 0.5 d for the prediction of unknown data. Retrospective simulations over 1961–2022 indicated earlier budburst as a consequence of ongoing climate warming. However, simulations revealed no significant change for the duration of budburst (DurBB, i.e., the time interval from BP20 to BP80 (with BP representing budburst percent), which respectively represent the date when 20 % and 80 % of trees in a population have reached budburst), due to a lack of significant temperature increase during DurBB in the past. This work can serve as a basis for the development of models targeting intra-population variability of other functional traits, which is of increasing interest in the context of climate change.