Cork thickness data are usually taken at each cork harvest from trees growing in plots. This hierarchical structure favours the use of a multi-level linear mixed approach. Mixed models include a fixed functional part, common to the whole popula- tion, and random components that allow us to divide and ex- plain the di ﬀ erent sources of stochastic variability which are not explained by the fixed part of the model. Another advan- tage of the mixed models is that they allow calibration of mod- els for a specific location and period from a small additional sample of observations. The mixed model approach was pro- posed by Vázquez  for modelling single tree cork weight. Empirical experience has shown that cork oak trees which produce good cork quality, tend to maintain this standard in successive strippings throughout their productive life . In the same way, it has been observed that there are productive areas, where trees tend to have greater cork thickness, and that these areas retain their productivity level throughout the cy- cle. Finally, it is also possible to identify good and bad periods for cork thickness, probably due to climatic e ﬀ ects . All these facts indicate that some unobservable tree factors (e.g., microsite or genetics), plot factors (ecological conditions or silviculture) or period e ﬀ ects (climatic conditions) a ﬀ ect tree cork thickness, even over long periods . This allows us to calibrate cork thickness models for present and future cork harvests by introducing predicted stochastic e ﬀ ects into the model which are specific to each source of variability.