Objective To construct and validate a predictive model for protein-energy wasting (PEW) in patients undergoing continuous ambulatory peritoneal dialysis (CAPD).  Methods  A total of 382 CAPD patients treated at the First Teaching Hospital of Tianjin University of Traditional Chinese Medicine from May 2025 to July 2025 were enrolled as study subjects, and relevant data were collected. The patients were randomly divided into a training set (267 cases) and a validation set (115 cases) at a 7:3 ratio. The training set was further divided into a PEW group and a non-PEW group. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were performed to screen for predictive variables. A nomogram model for predicting PEW in CAPD patients was then constructed using Logistic regression. The discriminative ability of the model was assessed using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated using the Hosmer-Lemeshow test.  Results   Univariate analysis revealed that age (Z=    -3.565, P<0.001), sex (χ²=4.157, P=0.041), body mass index (BMI) (Z=-6.446, P<0.001), employment status (χ²=5.989, P=0.014), handgrip strength (Z=-4.578, P<0.001), social support (χ²=8.246, P=0.016), depression (χ²=38.272, P<0.001), hemoglobin (Z=-2.790, P=0.005), albumin  (Z=-5.223, P<0.001), triglycerides  (Z=-2.222, P=0.026), creatinine (Z=-2.983, P=0.003), and serum potassium (Z=-1.981, P=0.048) were potential factors associated with PEW in CAPD patients. LASSO regression further refined the selection to five key predictive variables for PEW: BMI (coefficient: -0.125), handgrip strength (-0.006), social support level(-0.033), depression level (0.665), and albumin (-0.088). The AUC values for the training set and validation set were 0.852 (95% CI: 0.805～0.899) and 0.875 (95% CI: 0.813～0.937), respectively. The Hosmer-Lemeshow test indicated good calibration (training set: χ²=10.224, P=0.250; validation set: χ²=6.961, P=0.541).  Conclusion  The nomogram model constructed in this study demonstrates good predictive performance, which may facilitate early clinical identification of high risk PEW patients and provide a basis for decision making in individualized nutritional intervention.