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Cachexia affects approximately 50–80 % of advanced cancer patients, particularly those with gastric cancer (GC). Therefore, early detection of cachexia is essential to prevent its progression. Targeting the gut microbiota may be a promising approach for preventing and treating cachexia in patients with GC. Chemotherapy significantly reduced gut microbiota diversity in GC patients. Specifically, the abundance of bacterial genera such as Bacteroides , Streptococcus , and Prevotella was increased in the gut of patients postchemotherapy, which was closely associated with the development of cachexia. Serum metabolic analysis revealed a strong link between specific microbes and metabolite in patients with chemotherapy-induced GC cachexia. We further constructed a random forest model based on the top 6 genera in terms of abundance for the prediction of chemotherapy-related GC cachexia development; this model had an area under the receiver operating characteristic curve (AUC) of 93.5 % [95 % confidence interval (CI), 86.6 %-100 %], with a specificity and accuracy above 75 %. Additionally, we identified Enterotoxin Bacteroides fragilis (ETBF) as a key factor in chemotherapy-induced GC cachexia. In an in vivo GC model, the colonization of ETBF in the intestines of mice significantly accelerated the muscle and adipose tissue consumption induced by chemotherapy, resulting in cachexia symptoms. Furthermore, ETBF damaged the intestinal mucosal barrier by disrupting cell connections and attracting M1 macrophages, which advances GC cachexia. In conclusion, our findings indicate that gut microbiota imbalance is crucial in GC cachexia development, suggesting potential biomarkers for early diagnosis. Clinical trial registration: http://www.chictr.org.cn , Identification No: ChiCTR2200064547 [Display omitted] • Intestinal microbiota imbalance and metabolic disorders significantly contribute to cancer cachexia. • ETBF causes endotoxaemia by directly disrupting the intestinal mucosal barrier and indirectly releasing toxins. • ETBF promotes GC cachexia by recruiting intestinal macrophages to influence the intestinal immune microenvironment. • A random forest prediction model offers the possibility of predicting the potential clinical population of GC cachexia. [ABSTRACT FROM AUTHOR]