Important progresses have been made in palaeo- climatological studies by using statistical methods. But they are in somewhere limited as they take the present as an ab- solute reference. This is particularly true for the modern analogue technique. The availability of mechanistic mod- els to simulate the proxies measured in the sediment cores gives now the possibility to relax this constraint. In particu- lar, vegetation models provide outputs comparable to pollen data (assuming that there is a relationship between plant pro- ductivity and pollen counts). The input of such models is, among others, climate. The idea behind paleo-climatological reconstructions is then to obtain inputs, given outputs. This procedure, called model inversion, can be achieved with ap- propriate algorithms in the frame of the Bayesian statistical theory. But we have chosen to present it in an intuitive way, avoiding the mathematics behind it. Starting from a rela- tive simple application, based on an equilibrium BIOME3 model with a single proxy (pollen), the approach has evolved into two directions: (1) by using several proxies measured on the same core (e.g. lake-level status and δ13C) when they are related to a component of the vegetation, and (2) by us- ing a more complex vegetation model, the dynamic vegeta- tion model LPJ-GUESS. Examples presented (most of them being already published) concern Last Glacial Maximum in Europe and Africa, Holocene in a site of the Swiss Jura, an Eemian site in France. The main results are that: (1) pollen alone is not able to provide exhaustive information on precip- itation, (2) assuming past CO2 equivalent to modern one may induce biases in climate reconstruction, (3) vegetation mod- els seem to be too much constrained by temperature relative to precipitation in temperate regions. This paper attempts to organise some recent ideas in the palaeoclimatological re- construction domain and to propose prospectives in that ef- fervescent domain.