This paper presents a novel synchronization condition for coupled oscillator networks, applicable to both biological and engineered systems, including power grids. The synchronization condition is derived based on the network topology and parameters, and it is shown to be exact for various network structures and statistically valid for most networks. The condition is expressed in terms of the network Laplacian matrix and the natural frequencies of the oscillators, and it provides a clear criterion for determining whether a network will synchronize. The condition is validated through both analytical and numerical studies, and it is shown to be effective in predicting synchronization in complex networks and in smart grid applications. The synchronization condition is also shown to be applicable to a wide range of network topologies and parameters, and it is demonstrated to be robust in the face of network perturbations and varying load conditions. The results highlight the importance of synchronization in power systems and provide a practical tool for assessing the stability and robustness of power networks under different operating conditions. The synchronization condition is also shown to be applicable to other synchronization phenomena, including those in biological systems and social networks. The paper concludes with a discussion of the implications of the results for future research and applications in synchronization theory and power systems engineering.This paper presents a novel synchronization condition for coupled oscillator networks, applicable to both biological and engineered systems, including power grids. The synchronization condition is derived based on the network topology and parameters, and it is shown to be exact for various network structures and statistically valid for most networks. The condition is expressed in terms of the network Laplacian matrix and the natural frequencies of the oscillators, and it provides a clear criterion for determining whether a network will synchronize. The condition is validated through both analytical and numerical studies, and it is shown to be effective in predicting synchronization in complex networks and in smart grid applications. The synchronization condition is also shown to be applicable to a wide range of network topologies and parameters, and it is demonstrated to be robust in the face of network perturbations and varying load conditions. The results highlight the importance of synchronization in power systems and provide a practical tool for assessing the stability and robustness of power networks under different operating conditions. The synchronization condition is also shown to be applicable to other synchronization phenomena, including those in biological systems and social networks. The paper concludes with a discussion of the implications of the results for future research and applications in synchronization theory and power systems engineering.