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Background: The present study aimed to establish and validate a nomogram model to predict the occurrence of metachronous peritoneal metastasis (m-PM) in colorectal cancer (CRC) within 3 years after surgery. Method: The clinical datum of 965 patients were enrolled in this study from Second Hospital of Jilin University, between January 1, 2014 and January 31, 2019. The patients were randomly divided into training and validation cohorts at a ratio of 2:1. The least absolute shrinkage and selection operator (LASSO) regression was performed to identify the variables with nonzero coefficients to predict the risk of m-PM. Multivariate logistic regression was used to verify the selected variables and to develop the predictive nomogram model. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, Brier score, and decision curve analysis (DCA) were used to evaluate discrimination, distinctiveness, validity, and clinical utility of this nomogram model. The model was verified internally using bootstrapping method and verified externally using validation cohort.Results: The nomogram included 7 predictors: emergency operation, tumor site, histological type, pathological T stage, CA125, BRAF mutation and MSI status. The model achieved a good prediction accuracy on both the training and validation datasets. The C-index, area under the curve (AUC), and Brier scores were 0.814, 0.814 (95%CI 0.764–0.864), and 0.079, respectively, for the training cohort were 0.812, 0.812 (95%CI 0.732–0.893) and 0.087, respectively. DCA showed that when the threshold probability was between 0.01 and 0.75, using this model to predict m-PM could achieve a net clinical benefit.Conclusion: we have established and validated a nomogram model to predict m-PM in patients undergoing curative surgery, which shows good discrimination and high accuracy.Trial registration: The study was approved by Ethics Committee of the Second Hospital of Jilin University (Approval No.2021003) on January 19th.