This paper explores the critical intersection of financial stability and optimal bailout strategies. Our research is grounded in the Eisenberg-Noe model, a key framework for understanding the propagation of distress in interconnected financial institutions. We extend this model to examine the role of network analysis in the inter-bank borrowing and lending market, underscoring its significance in risk assessment and policy-making. Our study has three primary contributions. First, we identify essential factors influencing optimal bailout allocation decisions in the context of complex financial network. Second, we evaluate the predictive power of these factors through extensive numerical experiments. Finally, we validate our theoretical model using both simulated and real-world financial data, demonstrating an improved accuracy in forecasting bailout decisions compared to existing methodologies. This research not only advances the understanding of financial risk management but also contributes to developing more effective financial intervention strategies in times of crisis. By bridging the gap in understanding bailout decision-making processes within the Eisenberg-Noe model, our findings offer valuable insights for policymakers and researchers.