Dr.A.Anil Kumar Reddy,K.Vanajakshi,K.Akhila 02 05(1) Capital management is central to ensuring a companys longterm solvency growth and ability to maximize shareholder value It involves balancing equity and debt financing maintaining optimal liquidity and making strategic decisions regarding asset utilization and retained earnings Traditionally capital management analysis relies on financial ratios trend analysis and static models However such methods often fail to capture complex dynamic interactions among internal financial policies market conditions and macroeconomic changesThis study begins with a comprehensive review of capital structure working capital policy and dividend decisions to assess their collective impact on firm performance To enhance the analysis Machine Learning ML techniques like Random Forest and XGBoost are used to predict capital adequacy and optimal debtequity mix while Deep Learning DL models like LSTM networks forecast future capital requirements based on historical financial data and market trends By integrating these AIdriven approaches the study reveals nonlinear dependencies and patterns overlooked by traditional models offering richer more actionable insights for managers and investors alike Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026