Predictive Nasal Models for Northwest Indian Population

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Predictive Models for Nasal Profile in Forensic Facial Approximation: A Study on Northwest Indian Population

Organized by: International Forensic Scientist Awards
Website: forensicscientist.org

15th Edition of Forensic Scientist Awards 27-28 October 2025 | Paris, France

Forensic facial approximation (FFA) plays a vital role in the identification of unknown human remains, particularly when conventional methods such as DNA profiling or fingerprint analysis are not possible. This research focuses on the development of predictive models for nasal profiles based on age and sex variations in a Northwest Indian population, offering new insights into forensic reconstruction techniques.

Objectives

The primary aim of this study was to analyze age- and sex-related differences in nasal morphology and establish accurate regression models that can predict nasal features for forensic facial approximation. This work contributes to improving the precision and reliability of facial reconstruction methods in the Indian demographic context.

Materials and Methods

A total of 417 adult participants (208 males and 209 females), aged between 18 and 80 years, were included in the study. Using retrospective CT scan data, both soft and hard tissue nasal measurements were obtained.

The data were analyzed using:

  • Descriptive statistics for basic morphometric evaluation

  • Multivariate regression models to predict nasal dimensions

  • Discriminant function analysis (DFA) to assess classification accuracy based on sex and age

Results

The analysis revealed significant sexual dimorphism in nasal morphology, with males generally exhibiting broader and more projected nasal profiles compared to females.

Key findings include:

  • Strong correlations between cranial landmarks and nasal measurements

  • High predictive accuracy for nasal width and projection (adjusted R² = 0.68–0.80)

  • DFA classification accuracy of 92.4% (original data) and 91.3% (cross-validation), confirming the robustness of the model

Conclusion

This study highlights the critical role of age and sex in predicting nasal morphology for forensic facial approximation. The developed models serve as valuable forensic tools for enhancing the accuracy of human identification in the Northwest Indian population.

By integrating morphometric analysis and predictive modeling, this research bridges the gap between anthropometry and forensic reconstruction, paving the way for more scientifically grounded facial approximation techniques in forensic science.

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