This study provides one of the most strong and knowledge-driven assessments of mud loss prediction thus far, offering functional insights into the elaborate interaction of drilling parameters and demonstrating a predictive accuracy that considerably surpasses common empirical or much less advanced modeling techniques. This work aims to bridge t