Charcoal analysis aims to study different aspects of forest management, techno-economical choices and their specific impact on past landscapes, as well as the impact of climatic events. However, at the present time, charcoal analysis is generally limited to the study of a list of taxa and their relative frequency, as the methods usually employed in dendrochronology to characterize past woodland, based on long tree-ring series, are not suitable for anthracological material. Today, the new challenge for charcoal analysis is thus to develop adapted dendrological tools. In this context, the aim of the ANR DENDRAC project “Development of dendrometrical tools applied to anthracology: study of the interactions between Man, resources and environments” was to characterize modern-day wood stands in accordance with historical woodland practices and convert dendroecological data into parameters adapted to charcoal analysis. The purpose of this study is to define the dendrological features with the help of the anthracological tools without explaining the observed differences between the sampled stands (given the stational variability, age and regeneration modes). The first step consisted in creating dendro-anthracological tools based on morpho-anatomical criteria that help to characterize growth, distinguish heartwood from sapwood and evaluate charcoal-pith distance. The second step involves characterizing three modern-day wood stands (coppice under standard, high forest and young stand formed by a mixture of seeded and coppice trees), defined by their structure, stand density and regeneration modes, using dendrological data measured on fresh wood material and modelled into anthracological data with the dendro-anthracological tools. In this way, anthracological types were defined for each wood stand, forming anthraco-typological models, which area useful for the interpretation of archaeological charcoal assemblages. Finally, an anthracological key is proposed to sort archaeological charcoal fragments in anthraco-groups before data processing.