Under conditions of market uncertainty, traditional project evaluation methods undervalue the importance of managerial flexibility and distort the representation of the real return on capital investments. The objective of this study is to develop a comprehensive methodology for dynamic assessment that integrates tools of financial engineering and strategic analysis to account for uncertainty and optionality. The research question is how to integrate cash flow uncertainty and managerial decisions into the strategic value of a project, thereby improving the quality of investment decisions. The novelty of the approach lies in operationalizing the link between risk, flexibility, and value through consistent metrics and procedures. The materials and methods include real options theory to monetize managerial flexibility, Monte Carlo simulation to transition from point estimates to distributional assessments, as well as scenario analysis to structure external trajectories. Empirical testing was conducted on a detailed high-tech project with volatility calibrated based on historical data and expert-assigned scenario probabilities. Option values were assessed through binomial and continuous models, after which they were aggregated with traditional NPV into an integrated strategic value. The procedures are reproducible and oriented toward application in capital budgeting. The results show that baseline discounted analysis yields a negative NPV of minus 5,43 million rubles, while Monte Carlo simulation indicates an average NPV of minus 5,21 million with a standard deviation of 21,55 million and a 35,7 percent probability of positive NPV. Scenario analysis reveals strong sensitivity: from minus 38,92 in the pessimistic case to 42,16 million in the optimistic scenario, with the baseline at minus 5,43 million. Option values for expansion, abandonment, and deferral amount to 12,87, 3.15, and 1.88 million respectively, which raises the integrated strategic value to 12.47 million and shifts the decision from rejection to acceptance. The discussion interprets the transition from static to dynamic assessment as a paradigm shift - from attempting to predict a single outcome to designing a portfolio of managerial options. Practically, this strengthens capital budgeting discipline, aligns managerial incentives with long-term value creation, and supports proactive risk management. Limitations are related to the hypothetical nature of the case, model assumptions, and the quality of input data. Future perspectives include validation on real transactions, extension to portfolios, Bayesian identification of uncertainties, and integration with stress testing.