Background: Facial features are known to be highly heritable, exhibiting remarkable resemblance within families across generations. This inheritance pattern has significant implications in fields such as forensics, where reconstructing facial characteristics from limited ancestral data can aid in identification and investigation Aims: This study aims to leverage artificial intelligence (AI) and machine learning techniques to conduct a comprehensive computational analysis of craniofacial heritability within Indian families. Methods: A dataset comprising facial photographs of three generations (grandparents, parents and children) from 51 Indian families were compiled. Computer vision algorithms were employed to extract precise anthropometric measurements from these images. Various statistical methods, including Pearson correlation, hypothesis testing (T-tests, ANOVA, chi-square) and dimensionality reduction techniques (PCA, PCoA), were applied to quantify intergenerational relationships. Furthermore, machine learning models, such as linear regression and random forest regression, were developed to predict descendant facial features from ancestral data.Results: Pearson Correlation Analysis revealed exceptionally strong positive correlations (r > 0.9) between ancestral and descendant facial measurements, supported by statistically significant p-values. Hypothesis tests failed to reject the null hypothesis of no difference between generations, indicating remarkable similarity. Dimensionality reduction visualizations depicted clustering patterns that illustrated familial resemblance and generational variations. Machine learning models achieved high predictive accuracy, with random forest regression outperforming linear regression, capturing complex non-linear hereditary patterns.Conclusions: This study demonstrates the powerful capabilities of AI and machine learning techniques in quantifying and elucidating the heritability of craniofacial morphology across generations. The findings conclusively establish that facial features are highly heritable within Indian families, with genetics playing a predominant role over environmental influences. These computational forensic methods advance our ability to reconstruct facial characteristics from  limited ancestral data, enhancing forensic investigations and deepening our understanding of phenotypic inheritance.