In networks of coupled oscillators, the aging transition refers to the evolution of collective behavior influenced by the gradual degradation of individual components. This phenomenon is studied using macroscopic order parameters derived under strong coupling conditions, which capture the overall dynamics of the network. The transition highlights how changes in the network’s structure and connectivity, influenced by factors like heterogeneity among oscillators and feedback mechanisms, affect its stability and functionality over time. Critical stability analysis based on these parameters identifies thresholds where the network shifts between different states, offering insights into its resilience and response to internal and external influences as it ages.