Egeland, T.; Marsico, F.

Kinship cases, ranging from standard paternity tests to complex Disaster Victim Identifications, are typically evaluated using likelihood ratios (LR) based on forensic genetic markers. However, genetic evidence alone often proves insufficient in certain scenarios, particularly when determining which individual is the parent and which is the child in a relationship pair, or when establishing distant familial connections. While forensic practitioners frequently incorporate supplementary evidence (SE), such as age, biological sex, or phenotypic traits, in these cases, this integration typically occurs informally, without rigorous probability estimation, compromising procedural transparency and reliability. Here, we present a comprehensive methodological framework that formally synthesizes forensic DNA evidence (FDE) with SE through innovative Markov chain models and customized transition matrices designed for various biological traits. This approach generates combined likelihood assessments expressed as LRs or posterior probabilities. Validation through both simulated and real-world case studies demonstrates that the systematic incorporation of SE substantially improves resolution accuracy in kinship determinations. To facilitate adoption, we have implemented this methodology in mispitools, an open-source R package available to the forensic community.