This repository provides data and associated codes for a data-driven framework that enables prediction of macroscopic properties of 2D cellular metamaterials, and identifies their connection to key morphological characteristics, as identified by the integration of machine-learning models (Random Forest and GAM) and interpretability algorithms (SHAP analysis).