Abstract Multifactorial age estimation is preferred over methods based on a single anatomical site. The main challenge of the multifactorial methods lies in calculating the overall prediction interval. This study compared the performance of two approaches to achieve this: the minimal age principle versus a Bayesian approach. MRI of the third molars, left hand/wrist, and sternal extremity of both clavicles were prospectively conducted in 335 healthy Austrian Caucasian males aged 13–24 years. Development was staged according to De Tobel et al. Multi‐factorial age estimation: A Bayesian approach combining dental and skeletal magnetic resonance imaging. Forensic Sci Int. 2020;306:110054. Applying the minimal age principle rendered a mean absolute error of 1.47 years, root mean square error of 1.81 years, mean width of the 95% prediction interval (PI) of 4.44 ± 2.49 years, and coverage of 68.7%. For the Bayesian approach, the results were 1.41, 1.80, 5.15 ± 1.94 years, and 81.5%, respectively. Higher inconsistency between the different age indicators was linked to a lower coverage probability in the minimal age principle, but not in the Bayesian approach. Moreover, higher inconsistency between age indicators was also linked to a higher probability of obtaining an impossible PI with the minimal age principle. Furthermore, applying the minimal age principle rendered 97.9%/81.0% correctly categorized adults (based on the point prediction of age/based on the PI) and 69.2%/85.6% correctly categorized minors. For the Bayesian approach, the results were 95.2%/76.2% and 81.5%/95.9%, respectively. In conclusion, the Bayesian approach outperformed the minimal age principle for multifactorial forensic age estimation, allowing the construction of more appropriate PIs and more correctly categorized minors.
Coreelman et al. (2026) studied this question.