Objective To develop a risk prediction model for urinary incontinence among female inpatients with type 2 diabetes, so as to provide a reference for developing targeted intervention. Methods The item pool of influencing factors for urinary incontinence in female inpatients with type 2 diabetes was determined through systematic literature review, which was used to form a questionnaire after expert consultation, then the questionnaire was utilized to investigate 536 female inpatients with type 2 diabetes. Risk predictors were screened by LASSO regression analysis, based on which multi-factor logistic regression analysis was conducted to further explore and develop a nomogram prediction model. Internal validation of the model was performed using Bootstrap calculation. Results Waist circumference, exercise years, water intake, urinary tract infection, chronic cough, constipation, reproductive system surgery, anxiety, diabetic neuropathy, glycosylated hemoglobin, and serum creatinine were the influencing factors of urinary incontinence in female inpatients with type 2 diabetes (all P<0.05). Then a nomogram model was constructed using the above factors, the area under the curve for predicting urinary incontinence in female inpatients with type 2 diabetes was 0.893 (95%CI: 0.866-0.919), and the area under the curve in internal validation was 0.881. Conclusion The nomogram model has good discrimination and calibration, which can intuitively and concisely provide individualized urinary incontinence risk prediction for female inpatients with type 2 diabetes.