Objective: This study aimed to develop and validate the Difficult Airway Prediction Score (DAPS), a comprehensive predictive tool for assessing the likelihood of encountering a difficult airway, ultimately enhancing patient safety and clinical decision-making in airway management. Methods: A systematic literature review identified predictive factors for difficult airways. Using a diverse dataset of 1,500 patients, the DAPS was developed, incorporating factors such as Mallampati score, thyromental distance, neck mobility, presence of teeth, and previous airway history. The DAPS was subsequently validated on an independent cohort of 800 patients, and its predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC). Results: The DAPS demonstrated excellent predictive accuracy, with an AUC of 0.88 in both the development and validation cohorts. The scoring system included factors with assigned scores, facilitating easy risk assessment. The DAPS's validation results confirmed its consistent performance across diverse patient populations and clinical settings. Conclusion: The Difficult Airway Prediction Score (DAPS) represents a significant advancement in airway management, empowering clinicians to proactively assess and manage difficult airways. Its reliability, generalizability, and potential for improving patient care emphasize its relevance in contemporary clinical practice.