Dr.K.Shiva Keshav Reddy,L.Yamuna,K.Padya sree 02 05(1) Reliance Industries Limited RIL and its telecom arm Reliance Jio represent two pillars of one of Indias largest and most diversified conglomerates Traditional financial analysis methodssuch as ratio analysis trend analysis and commonsize statementshelp assess profitability growth and financial health over time However these methods often fail to uncover deeper nonlinear patterns or accurately forecast future financial trends in dynamic sectors like telecom and energyThis study combines a conventional financial statement analysis of RIL and Jio with advanced predictive analytics We apply Machine Learning ML models including Random Forest and XGBoost to identify the key drivers of profitability and predict revenue and net profit based on historical financial data and macroeconomic factors Additionally Deep Learning DL models specifically Long ShortTerm Memory LSTM networks are employed to forecast timeseries trends in quarterly revenue and stock pricesOur results reveal how the performance of Jios highgrowth digital business contrasts with RILs diversified portfolio highlighting sectorspecific volatility and stability The integration of AIdriven models not only enhances forecasting accuracy but also uncovers hidden interactions between business segments market sentiment and external economic indicators The study underscores the transformative potential of combining traditional financial analysis with ML and DL to gain deeper strategic insights and improve forecasting precision Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026