Decision Tree Approach is a quantitative decision-making technique used to evaluate different alternatives under conditions of risk and uncertainty. It provides a graphical representation of decision options, possible future events, probabilities, and expected outcomes. In managerial applications, decision trees help managers analyze complex problems systematically and choose the alternative that maximizes expected benefits or minimizes expected costs. The method is widely used in finance, marketing, operations management, project evaluation, investment analysis, and strategic planning. A decision tree consists of decision nodes, chance nodes, branches, probabilities, and payoffs. A decision node, usually represented by a square, indicates a point where the decision-maker selects one among several alternatives. A chance node, represented by a circle, indicates uncertain events that occur with known or estimated probabilities. Branches connect nodes and represent possible actions or events. Payoffs indicate the financial return, profit, cost, or utility associated with each possible outcome. The decision tree approach begins with clearly defining the decision problem and identifying all feasible alternatives. The next step involves identifying uncertain events that may affect the outcome of each alternative. Probabilities are then assigned to these uncertain events based on historical data, expert opinion, or statistical analysis. Expected Monetary Value (EMV) is calculated by multiplying each possible payoff by its probability and summing the results.