Objective To explore the factors affecting the occurrence of transient arrhythmia after percutaneous coronary intervention （PCI） in patients with acute coronary syndromes （ACS）， to establish a risk prediction model， and to test the prediction effect. Methods 480 ACS patients who underwent PCI in Western Theater Air Force Hospital of PLA from August 2022 to February 2024 were selected as study subjects and were divided into 336 cases in the construct group and 144 cases in the validation group according to the ratio of 7：3. The data of the construct group were used to construct the model， and the validation group was used to validate the model. The patients in the constructed group were divided into 84 cases in the occurrence group and 252 cases in the non-occurrence group according to whether they had experienced postoperative transient arrhythmia， and the validation group was divided into 36 cases in the occurrence group and 108 cases in the non-occurrence group. The baseline data of the study subjects in the two groups were observed， and the predictive value of continuous variables was analyzed using the ROC experiment； the influencing factors of the occurrence of transient arrhythmia after PCI in ACS patients were analyzed using multifactorial logistic regression； the Nomogram prediction model was constructed using the R language； and the model was evaluated and validated using calibration curves and decision curves. Results The results of a one-way analysis of the constructed group showed that older age， the presence of a history of diabetes mellitus， the time from onset to admission ≥ 6 h， and higher BNP levels were the main risk factors for the occurrence of transient arrhythmia after PCI in patients with ACS （P < 0.05）， and the prediction model established accordingly had an AUC of 0.865 and a 95% CI of 0.804 ~ 0.927， which was effective in predicting the occurrence of transient arrhythmia after PCI in patients with ACS. The model performed well in predicting the occurrence of transient arrhythmia after PCI， with a C-index of 0.858 （0.753 ~ 0.865）， and provided a good standardized net benefit when its risk threshold was between 0.10 to 0.96. The validation group ROC curve and calibration curve results are good， with an AUC of 0.846 and a C-index of 0.840 （0.737 ~ 0.851）， suggesting that the model has a good external predictive efficacy. The results of the validation group decision curve analysis indicated that the model could provide better standardized net returns when the risk threshold was between 0.06 and 0.94. Conclusion The results of univariate analysis showed that older age， the presence of a history of diabetes mellitus， onset-to-admission time ≥6 h， and higher BNP levels were the main risk factors for the occurrence of transient arrhythmia after PCI in patients with ACS， and the Nomogram model constructed on the basis of these four influencing factors could effectively predict the risk of transient arrhythmia after PCI in patients with ACS.