Background: Stature estimation is a fundamental component of forensic identification and anthropological investigations. Although long-bone measurements provide the highest accuracy, they are not always available in cases involving fragmented or incomplete human remains. Anthropometric measurements of the hand and fingers offer practical alternatives because they are simple, inexpensive, and non-invasive. The little finger has been comparatively underexplored as a predictor of stature, particularly in South Indian populations. Objectives: To evaluate the relationship between little finger length and stature and to develop regression models for anthropometric estimation. Materials and Methods: A cross-sectional observational study was conducted among 105 healthy adults aged 18–40 years at Yenepoya Medical College. Standing height was measured using a stadiometer, while right and left little finger lengths were measured using a Vernier caliper following standard anthropometric techniques. Each measurement was recorded twice, and the average value was used for analysis. Pearson correlation and linear regression analyses were performed using Microsoft Excel. Statistical significance was set at p < 0.05. Results; Stature demonstrated a significant positive correlation with right little finger length (r = 0.484, p < 0.001) and left little finger length (r = 0.390, p < 0.001). Weight showed a significant correlation only with the right little finger (r = 0.328, p = 0.001), whereas BMI was not significantly associated with either measurement. Regression analysis identified height and gender as significant predictors of right little finger length (R² = 27.3%), while height alone significantly predicted left little finger length (R² = 15.2%). Discriminant analysis based on bilateral little finger lengths correctly classified 67.61% of participants according to sex. Conclusion: Little finger length demonstrates a statistically significant association with stature and may serve as a practical anthropometric parameter in forensic and anthropological applications. Population-specific regression models may improve the accuracy of stature estimation in situations where conventional skeletal measurements are unavailable.