While numerous methods exist for kinship determination, their results frequently show incomplete concordance. To improve accuracy and reliability, we employed a multi-analytical approach in this study. Using blood samples from 20 wild sheep (Ovis gmelini) at the Miankotal Captive Breeding Site (Fars Province, Iran), we conducted a comparative analysis of kinship inference models based on nuclear microsatellite data. Initial simulations assessed each locus's discriminatory power for kinship determination. Kinship relationships were evaluated using multiple parentage analysis software (COLONY, CERVUS, and ML-Relate) and relatedness indices. The OarFCB304 and McM527 ranked as the highest and lowest in terms of information content for relatedness estimation. Although we observed agreement between methods, some discrepancies emerged. CERVUS identified three parent–offspring pairs with high confidence, whereas classification of these samples using ML-Relate and COLONY mainly indicated sibling relationships. Despite the fact the most likely kinship pattern in the population was half-sibling relationships, it is essential to reduce the likelihood of inbreeding through management actions such as introducing new individuals into the population. This study demonstrates that an integrative analytical approach incorporating kinship indices, parentage analyses, and biological information yields a more precise understanding of population kinship structure.