<p>The management of multi-echelon forestry supply chains is fraught with uncertainties resulting from environmental variability, economic fluctuations, and regulatory changes. The uncertainties–manifested in volatile market demand, unpredictable resource availability, and fluctuating production and logistics costs–pose significant challenges to coordinated decision-making across supply chain echelons. Conventional deterministic and stochastic models often fail to capture the full spectrum of these uncertainties, particularly the inherent indeterminacy and contradictory information present in real-world forestry operations. Our study proposes a novel neutrosophic sequential game-theoretic model to address these challenges. Neutrosophic logic, which generalizes fuzzy logic by incorporating truth, indeterminacy, and falsity membership functions, provides a robust mathematical framework for representing and reasoning with complex uncertainties that exhibit partial truth, ambiguity, and contradiction simultaneously. The model captures the strategic interactions between key supply chain participants: forest owners, timber processors, distributors, and retailers, all within a sequential decision-making structure. Specifically, we formulate a Stackelberg game where players’ decisions are interdependent: the forest owner’s harvesting strategy influences the processor’s production plan, which in turn affects the distributor’s logistics and the retailer’s pricing and inventory decisions. As a result, by integrating neutrosophic variables into profit functions and constraints, our model enables the optimization of forest supply chain strategies under uncertainty, accounting for different degrees of truth, indeterminacy, and falsity. The proposed approach yields equilibrium solutions for pricing and production that improve both economic efficiency and environmental sustainability, demonstrating a capability to handle nuanced uncertainties in forestry supply chains compared to traditional optimization methods.</p>