Molecular crystals are ubiquitous—in organic electronics, pharmaceuticals, and agrochemicals—yet their mechanical behaviour is still poorly mapped. Mechanical properties of molecular crystals—elastic constants (Young’s, shear and bulk modulus/compressibility) and their strong anisotropy (direction dependence), together with mechanical robustness, govern manufacturability, solid-form stability during processing/handling stress, and enable elastically bendable organic functional crystals for flexible optoelectronics. However, complete experimental elastic tensors exist for only a tiny fraction of the hundreds of thousands of known crystal structures.ElastiCrys will develop a machine-learning interatomic potential tailored to molecular crystals and use it to compute full elastic tensors with quantified uncertainty. The resulting high-throughput pipeline will screen and analyse a large fraction of the Cambridge Structural Database (CSD), targeting ~500,000 high-quality, cleaned entries, and deliver an open, searchable database of elastic properties (a public “elasticity atlas”). The project will highlight outliers (exceptionally soft crystals, negative linear compressibility and other unusual responses) and validate the most promising predictions with targeted experiments, accelerating materials selection and enabling reproducible, FAIR-compliant research. The database will also provide a benchmark and training resource for future inverse design and generative discovery, helping the community move from trial-and-error to data-driven mechanical design.