Background <p>The increasing prevalence of pregnancies complicated by macrosomia presents a significant challenge in obstetric care. Biometry-based formulas have limitations, especially in extremes of weights; hence, refinement of these models and consideration of additional variables could improve reliability of ultrasound estimates of BW in macrosomic fetuses as accurate estimation of fetal weight is crucial for optimizing management and minimizing risks.</p> Objective <p>This study aimed to develop a reliable model for estimating fetal weight in LGA fetuses by incorporating maternal body mass index (BMI), abdominal wall thickness and diabetic status alongside standard biometric parameters.</p> Methods <p>A prospective, cross-sectional study was conducted at a tertiary care center from May 2022 to June 2024, involving 210 pregnant women. The study was divided into two phases: the model derivation phase (<i>n</i> = 140) and the validation phase (<i>n</i> = 70). Fetal biometric parameters were measured using 2D ultrasonography. The new formula was statistically analyzed for accuracy and precision and compared with existing models.</p> Results <p>The model achieved 95.7% accuracy within 10% of the actual BW during validation, significantly outperforming existing models, including Hadlock 1985. The incorporation of maternal parameters improved predictive precision, with a low systemic error and moderate standard deviation.</p> Conclusion <p>Integrating maternal BMI, abdominal wall thickness and diabetic status enhances the accuracy of fetal weight estimation in macrosomic cases. These findings support improved clinical decision-making and could help reduce maternal and neonatal morbidity. Future studies with larger cohorts are necessary to validate the model further and establish clear criteria for its application.</p>