The flexible electron configurations in d or f orbitals in transition metals define new bonding patterns which differentiate them from covalent bonds in organic molecules. Metal-ligand bonding is very complex, with a wide variety of coordination nubmers. Moreover, ligand-ligand and metal-metal interactions also pose challenges in the design of organometallic compounds. On the other hand, the intricate structural features of organometallic complexes imparts important and novel properties to transition metal complexes (TMCs). For example, the spin states of transition metals remain of great interest, with increasing interest in the determination of the preferred ground spin state and on the factors that influence the preferred spin state and the overall energetics of the various possible spin states. The existence of multiple energetically accessible spin states in transition metal complexes enriches the diversity of TMCs, leading to numerous technological applications. Taken together, these features of TMCs motivates the active exploration of unknown complexes with optimal properties. The discovery of novel structures in transition metal chemistry involves several steps, including computational design/validation, experimental synthesis/testing with a focus on practical applications. In this review, we focus on the ongoing development of computational strategies with particular emphasis on artificial intelligence(AI)/machine learning(ML) for the design of novel TMCs. Traditional computational approaches leverage explicit chemical principles with human intuition and expertise for rational in silico complex design. The detailed analysis obtained from these computational methods are valuable resources to guide the inverse design of new molecules. The rapid development of DFT methods facilitates the extensive investigation of electronic structure data derived from TMCs. However, for the large-scale screening of promising complex systems. And this capability is particularly beneficial in tasks such as drug discovery, material design, and process optimization, where speed and precision are crucial.