The study of past societies requires describing and explaining patterns and their dynamics (diffusion of materials, settlement organization, raw material exchanges, biological indicators of landscape changes, etc.) in a multi-dimensional spatio-temporal environment from incomplete, ambiguous and heterogeneous datasets, which often lead to (retro)prediction. Though traditional methods remain important to investigate material culture complexes and past human societies over time and space, novel quantitative approaches based on computational modeling are rapidly gaining momentum. Researchers can rely nowadays on multi-modelling approaches from various backgrounds, including conceptual models, data mining and data- driven analysis (e.g. machine learning and stochastic models), spatial analysis and computer simulations, at different stage of the work process. In such context, this special collection aims at exploring challenges and opportunities offered by bringing together traditional archaeological questions with the most cutting edge technological applications.