One third of contemporary tropical forests is designated by national forest services for timber production. Tropical forests are also increasingly affected by anthropogenic disturbances. However, there is still much uncertainty around the capacity of tropical forests to recover their timber volume after logging as well as other disturbances such as fires, large blow-downs and extreme droughts, and thus on the long-term sustainability of logging. We developed an original Bayesian hierarchical model of Volume Dynamics with Differential Equations (VDDE) to infer the dynamic of timber volumes as the result of two ecosystem processes: volume gains from tree growth and volume losses from tree mortality. Both processes are expressed as explicit functions of the forest maturity, i.e. the overall successional stage of the forest that primarily depends on the frequency and severity of the disturbances that the forest has undergone. As a case study, the VDDE model was calibrated with data from Paracou, a long-term disturbance experiment in a neotropical forest where over 56¿ha of permanent forest plots were logged with different intensities and censused for 31 years. With this model, we could predict timber recovery at Paracou at the end of a cutting cycle depending on the logging intensity, the rotation cycle length, and the proportion of commercial volume. The VDDE modelling framework developed presents three main advantages: (i) it can be calibrated with large tree inventories which are widely available from national forest inventories or logging concession management plans and are easy to measure, both on the field and with remote sensing; (ii) it depends on only a few input parameters, which can be an advantage in tropical regions where data availability is scarce; (iii) the modelling framework is flexible enough to explicitly include the effect of other types of disturbances (both natural and anthropogenic: e.g. blow-downs, fires and climate change) on the forest maturit