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Sichuan Province is located at the transitional junction regions of the Qinghai-Tibet Plateau and the low-altitude plains. It also serves as the corridor of Sino-Tibetan-speaking population migration and expansion since neolithic expansion of Proto-Tibeto-Burman populations from Middle/Upper Yellow River during Majiayao period (3300–2000 BC). However, the population structure and the corresponding genetic diversity of forensic-related markers in this region remain unclear. Thus, we genotyped 30 insertion-deletion (InDel) markers in 444 samples from four ethnic groups (Han, Tibetan, Hui and Yi) from Sichuan Province using the Investigator® DIPplex kit to explore the characteristics of population genetics and forensic genetic focuses. All the loci were found to be in Hardy-Weinberg Equilibrium (HWE) after applying a Bonferroni correction and no pairwise loci showed prominent linkage disequilibrium. The combined matching probability (CMP) and the combined power of discrimination (CPD) are larger than 1.8089 × 10−11 and 0.99999999995, respectively. Principal component analysis, Multi-Dimensional Scaling Plots and Neighbour-Joining tree among 65 worldwide populations indicated that Sichuan Hui and Han are genetically close to Hmong-Mien and Tai-Kadai-speaking populations, and Sichuan Tibetan and Yi bear a strong genetic affinity with Tibeto-Burman-speaking populations. The model-based genetic structure further supports the genetic affinity between the studied populations and linguistically close populations.Key Points Forensic parameters of 30 insertion-deletions (InDels) in 444 individuals from four populations are reported, which showed abundant genetic affinity and diversity among populations and high value in personal identification. Genetic similarities existed between the studied populations and ethnically, linguistically close populations. Sichuan Hui and Han are genetically close to Hmong-Mien and Tai-Kadai-speaking populations. Sichuan Tibetan and Yi bear a strong genetic affinity with Tibeto-Burman-speaking populations.