Lithium-sulfur (Li-S) batteries are notable for their high theoretical energy density, but the ‘shuttle effect’ and the limited conversion kinetics of Li-S species can downgrade their actual performance. An essential strategy is to design anchoring materials (AMs) to appropriately adsorb Li-S species. Herein, we propose a new three-procedure protocol, named InfoAd (Informative Adsorption) to evaluate the anchoring of Li₂S on two-dimensional (2D) materials and disclose the underlying importance of material features by combining high-throughput calculation workflow and machine learning (ML). In this paradigm, we calculate the anchoring of Li₂S on 1255 2D A_xB_y (B in the VIA/VIIA group) materials and pick out 44 (un)reported nontoxic 2D binary A_xB_y AMs, in which the importance of the geometric features on the anchoring effect is revealed by ML for the first time. We develop a new Infograph model for crystals to accurately predict whether a material has a moderate binding with Li₂S and extend it to all 2D materials. Our InfoAd protocol elucidates the underlying structure–property relationship of Li₂S adsorption on 2D materials and provides a general research framework of adsorption-related materials for catalysis and energy/substance storage.