Few predictive biomarkers exist for identifying patients who may benefit from neoadjuvant therapy (NAT). The intratumoral microbial composition is comprehensively profiled to predict the efficacy and prognosis of patients with esophageal squamous cell carcinoma (ESCC) who underwent NAT and curative esophagectomy. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis is conducted to screen for the most closely related microbiota and develop a microbiota-based risk prediction (MRP) model on the genera of TM7x, Sphingobacterium, and Prevotella. The predictive accuracy and prognostic value of the MRP model across multiple centers are validated. The MRP model demonstrates good predictive accuracy for therapeutic responses in the training, validation, and independent validation sets. The MRP model also predicts disease-free survival (p = 0.00074 in the internal validation set and p = 0.0017 in the independent validation set) and overall survival (p = 0.00023 in the internal validation set and p = 0.11 in the independent validation set) of patients. The MRP-plus model basing on MRP, tumor stage, and tumor size can also predict the patients who can benefit from NAT. In conclusion, the developed MRP and MRP-plus models may function as promising biomarkers and prognostic indicators accessible at the time of diagnosis. The microbiota-based risk prediction (MRP) model and the integrated MRP-plus model, incorporating MRP, tumor stage, and tumor size, are devised to discern patients suitable for neoadjuvant therapy (NAT) and prognostic outcomes for those with ESCC. Both the MRP and MRP-plus models can be practical and reliable tools for guiding treatment strategies in ESCC patients. image