Objective To evaluate the diagnostic accuracy of tandem mass spectrometry (MS/MS) combined with artificial intelligence (AI) for neonatal methylmalonic acidemia (MMA), and to identify factors associated with diagnostic accuracy. Methods A total of 246 neonates with positive initial MMA screening at Qinhuangdao Maternal and Child Health Hospital from January 2019 to December 2024 were recalled for confirmatory testing. Using genetic diagnosis as the reference standard, all cases underwent MS/MS diagnosis, AI diagnosis, and combined diagnosis (MS/MS plus AI). Sensitivity, specificity, accuracy, and other diagnostic performance indices were calculated; agreement with genetic diagnosis was assessed; and multivariable logistic regression was performed to identify factors associated with diagnostic accuracy. Results The combined diagnosis yielded a sensitivity of 92.3%, a specificity of 97.0%, and an accuracy of 96.7%, with high agreement with genetic diagnosis (Kappa=0.733). The areas under the receiver operating characteristic curve for combined, MS/MS, and AI diagnoses were 0.914(95%CI: 0.867-0.935), 0.759(95%CI: 0.635-0.816), and 0.669(95%CI: 0.584-0.776), respectively; the area under the curve for the combined diagnosis was significantly higher than that for either MS/MS or AI alone (P<0.05). Lower levels of methionine, phenylalanine, ornithine, glycine, blood ammonia, and lactic acid, as well as abnormal electrophysiological findings, were independently associated with diagnostic accuracy (P<0.05). Conclusions MS/MS combined with AI shows high diagnostic accuracy for neonatal MMA. Lower levels of methionine, phenylalanine, ornithine, glycine, blood ammonia, and lactic acid and abnormal electrophysiological findings may affect the diagnostic accuracy of MMA.