A research team from Beijing University of Science and Technology developed an alloy design strategy combining machine learning and the CALPHAD method to address the high residual stress and crack sensitivity challenges of additively manufactured superalloys. This approach comprehensively considers microstructure stability, printability, oxidation resistance, density, and mechanical properties. The study successfully developed a γ′-strengthened Co-Ni base superalloy, which achieved crack-free components with relative density exceeding 99.9% via selective laser melting on an unheated substrate. It also demonstrated a superior strength-ductility balance compared to existing high γ′ volume fraction additively manufactured superalloys. The research indicates that γ′-strengthened Co-Ni base superalloys, with a narrower solidification range and lower γ′ solvus temperature than nickel-based alloys, are more suitable for additive manufacturing.