Broadly neutralizing antibodies (nAbs) are vital therapeutic tools to counteract both pandemic and seasonal influenza threats. Traditional strategies for optimizing nAbs generally rely on labor-intensive, high-throughput mutagenesis screens. Here, we present an innovative structure-based design framework for the optimization of nAbs, which integrates epitope-paratope analysis, computational modeling, and rational design approaches, complemented by comprehensive experimental assessment. This approach was applied to optimize MEDI8852, a nAb targeting the stalk region of influenza A virus hemagglutinin (HA). The resulting variant, M18.1.2.2, shows a marked enhancement in both affinity and neutralizing efficacy, as demonstrated both in vitro and in vivo. Computational modeling reveals that this improvement can be attributed to the fine-tuning of interactions between the antibody’s side-chains and the epitope residues that are highly conserved across the influenza A virus HA stalk. Our dry-wet iterative protocol for nAb optimization presented here yielded a promising candidate for influenza intervention.