The volatility and capital intensity of the oil and gas industry demand financial strategies that are not only internally coherent but also externally aligned with macroeconomic realities. This paper proposes a structured forecasting model that integrates key macroeconomic indicators—such as crude oil prices, inflation, interest rates, exchange rates, and GDP trends—into the long-term financial strategy of oil and gas enterprises. The model is designed as a modular framework comprising data acquisition, indicator analysis, and strategic translation components. It prioritizes indicators based on industry sensitivity, predictive power, and volatility exposure, and applies dynamic weighting to enhance responsiveness to economic fluctuations. Through scenario alignment, the model enables firms to prepare for multiple economic trajectories, improving capital allocation, investment timing, and risk mitigation. The study also explores the strategic implications of macroeconomic-informed planning, including improved financial resilience, more accurate return-on-investment forecasting, and enhanced transparency in financial governance. By translating complex economic trends into actionable strategic insights, the model empowers CFOs, planners, and policymakers to make proactive, data-driven decisions. The conclusion outlines future pathways for model refinement, including AI-based automation and cross-industry adaptation, underscoring the model’s relevance as both a practical tool and a foundation for further research in financial foresight.