Abstract: 【Objective】To explore the intestinal microbiota and network structure characteristics of Xingyi bantam chickens with different body weight groups, and identify potential biomarkers related to body weight, providing a theoretical basis for the discovery of growth-promoting probiotics in the chicken industry. 【Method】Selected 20 chickens each with the highest and lowest body weight from 110 hens(16 weeks old) to construct the high body weight group(HWC, 1.12 ±0.05 kg) and the low body weight group(LWC, 0.74±0.05 kg). Collected anal stool samples to detect the V3-V4variable region of the 16S rRNA sequence. Mothur was used to measure the alpha diversity of the intestinal microbiota.Principal coordinate analysis(PCoA) based on the unweighted UniFrac distance was used to evaluate the beta diversity of the intestinal microbiota. And microbial interaction network was constructed using the SparCC algorithm for the sequencing data. Finally, LEfSe analysis was used to identify intestinal microbes related to Xingyi bantam chicken body weight.【Result】The results showed that a total of 3145511 Clean reads were obtained from 40 Xingyi bantam chicken stool samples, and 22297 amplicon sequence variants(ASVs) were obtained through DADA2 cluster analysis. The intestinal microbiota of Xingyi bantam chickens mainly included Firmicutes(relative abundance 67.54%), Proteobacteria(relative abundance 12.24%), Bacteroidota(relative abundance 11.28%), Actinobacteriota(relative abundance 2.39%), and Desulfobacterota(relative abundance 1.26%) at the phylum level, At the genus level, mainly included Lactobacillus(relative abundance 23.35%), Rothia(relative abundance 14.86%), Ligella(relative abundance 5.44%), Bacteroides(relative abundance 4.63%), and Shigella(relative abundance 2.77%). The stability index of the intestinal microbiota of Xingyi bantam chickens in the LWC group was 3.95%, and that of the HWC group was 12.22%. Interaction network analysis found that the complexity of gut microbial network in LWC(5.57%) was lower than that of HWC(7.70%). It was speculated that the decrease of intestinal microbiota complexity and stability of low body weight Xingyi bantam chickens was related to the lower body weight. The top 5 hub microbiota with the highest importance scores in the interaction network of intestinal mircribuita of Xingyi bantam chickens were Lactobacillus plantarum, Lactococcus, Ruminococcus twisted chain group, Faecalibacterium, and Rikenellaceae_RC9_gut_group. In addition, LEfSe analysis found that relative abundance of 18 ASVs were significantly different between the two groups(LDA>2, P<0.05). Among them, 12 ASVs showed higher relative abundance in the LWC group than HWC group. The relative abundance of 6 ASVs in the HWC group was higher than that in the LWC group. 【Conclusion】The increase in the relative abundance of harmful bacteria such as Enterobacteriaceae and Mycoplasma can reduce the stability and complexity of the intestinal microbial interaction network in Xingyi bantam chickens, which may be the reason for the low body weight. Lactobacillus, Rikenellaceae_RC9_gut_group,Clostridium_sensu_ stricto_1 are the potential key microbiota affecting the body weight of Xingyi bantam chickens, they can be used as a candidate biomarker associated with body weight of Xingyi bantam chickens.