In developing economies, the stock market plays a vital role in capital formation and economic development. Forecastingstockprice movements remains a challenging yet crucial task for investors and researchers due to the inherent stochastic nature andvolatilityofstock prices. This study employs a Markov Chain (MC) model to analyze and predict the price trend of ITC Ltd. shares tradedontheNational Stock Exchange (NSE) of India. A two-state Markov model was constructed using 700 days of historical dailyclosingprices,with states defined as “Increase” and “Decrease” based on day-to-day price changes. Initial and transition probabilities werecomputed,and the long-term behavior of the stock was evaluated through steady-state probabilities and n-step transition matrices. Theanalysisreveals that the stock has approximately a 50% probability of increasing and a 49% probability of decreasing in the longrun. Thestudyfurther calculates the expected number of visits and return times for each state. The results demonstrate that the MarkovChainmodelcanserve as a reliable probabilistic framework for stock trend forecasting and can assist investors in making informeddecisions.Thisapproach offers significant utility for portfolio management and market risk analysis in the Indian equity context. Keywords:Markov Chain, Stock Market Forecasting, NSE, ITC Ltd., Transition Probability Matrix, Stationary Distribution