The design of novel organometallic complexes is highly demanding but worth the effort given their various applications. In this study, we described LigandDiff, a 3D-conditional diffusion model for transition metal complexes generation. LigandDiff designs realistic ligands under a set of given ligands and their associated metals and it is capable of generating novel and unique ligands which is relevant for molecular design. Moreover, we found LigandDiff to be transferable and can design ligands for transition metals that are not included in the training dataset. Overall, we believe this tool has potential to facilitate the design of novel organometallics for applications ranging from metallodrugs to materials.