Small bowel capsule endoscopy (SBCE) and balloon-assisted endoscopy (BAE) have revolutionized the diagnosis and treatment of small bowel bleeding (SBB), allowing access to the small bowel and identification of specific bleeding lesions. However, some patients experience rebleeding after small bowel investigation, and there are no definitive algorithms for determining the most appropriate follow-up strategy in SBB patients. We developed and validated a nomogram that can predict rebleeding risk and be used to develop a risk-stratified follow-up strategy in SBB patients. A retrospective study was performed using data from 401 SBB patients who underwent SBCE at Nagoya University Hospital. We developed and internally validated a predictive model for rebleeding in the form of a nomogram using Cox regression models and a bootstrap resampling procedure. Optimal risk factors were selected according to the least absolute shrinkage and selection operator (LASSO). The LASSO method identified 8 independent predictors of rebleeding that could be assessed to obtain a 'predicting rebleeding in SBB', or 'PRSBB' score: age, sex, SBB type, transfusion requirement, cardiovascular disease, liver cirrhosis, SBCE findings, and treatment. The c-statistic for the predictive model was 0.681. In conclusion, our PRSBB score can help clinicians devise appropriate follow-up plans.