Pulmonary function tests (PFTs) are pivotal in diagnosing and managing a broad spectrum of respiratory disorders. These tests provide critical insights into lung health, guiding diagnoses, assessing disease severity, and shaping patient management strategies. This review addresses the complexities and nuances inherent in interpreting PFT data, particularly in light of recent updates from the European Respiratory Society (ERS) and American Thoracic Society (ATS). These updates have refined interpretive strategies, moving away from definitive diagnostic uses of spirometry to a more probabilistic approach that better accounts for individual variability through the use of Z-scores and lower limits of normal (LLNs). Significantly, this narrative review delves into the philosophical shift in spirometry interpretation, highlighting the transition from direct clinical diagnostics to a more nuanced evaluation geared towards determining the likelihood of disease. It critiques the reliance on fixed ratios and emphasizes the need for reference values that consider demographic variables such as age, sex, height, and ethnicity, in line with the latest Global Lung Function Initiative (GLI) equations. Despite these advances, challenges remain in ensuring uniformity across different predictive models and reference equations, which can affect the accuracy and consistency of interpretations. This paper proposes a streamlined three-step framework for interpreting PFTs, aiming to unify and simplify the process to enhance clarity and reliability across various medical specialties. This approach not only aids in accurate patient assessments but also mitigates the potential for misdiagnosis and ensures more effective patient management. By synthesizing contemporary guidelines and integrating robust physiological principles, this review fosters a standardized yet flexible approach to PFT interpretation that is both scientifically sound and practically feasible.