Early warning indicators for multi-scale dynamics are essential tools for predicting critical transitions in complex systems that operate across different spatial and temporal scales. These systems,including ecosystems, climate systems, financial markets, and social structures can exhibit abrupt shifts due to interactions between local and global dynamics. Key EWIs such as \textit{critical slowing down}, characterized by increased autocorrelation ($\rho$) and variance ($\sigma^2$), and \textit{flickering}, which involves intermittent transitions between states, signal changes in system stability as tipping points approach. Spatial indicators like increased spatial autocorrelation and changes in patch-size distributions also provide insights into impending transitions. The emergence of patterns such as cross-scale synchronization and heightened sensitivity to perturbations indicates reduced resilience. Measures like multiscale entropy and observations of nonlinear responses further aid in detecting impending shifts. By monitoring these indicators, it is possible to anticipate transitions earlier and implement interventions to mitigate risks, thereby enhancing system resilience.