Objective To investigate the application value of serum lipoprotein (a) [LP(a)] and low-density lipoprotein cholesterol (LDL-C) in the prognostic evaluation of patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI). Methods The ACS patients who were hospitalized and underwent PCI in Yangzhou Jiangdu People's Hospital from January 2015 to December 2020 were enrolled as subjects, and all patients were followed up within the first year after PCI. Univariate and multivariate logistic regression analyses were used to investigate the influencing factors for the prognosis of ACS patients after PCI, and LP (a) and LDL-C were combined with related influencing factors to establish a risk predictive model for poor prognosis. In addition, Spearman's correlation coefficient was used to investigate the correlation of LP(a) and LDL-C with Gensini score. The ROC curve analysis and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive model. Results Among the 989 patients in this study, 385 (38.9%) experienced adverse cardiovascular events during follow-up. The univariate logistic model showed that age, carotid plaque, total length of PCI stent, coronary Gensini score, LP(a), triglyceride, and whether aspirin was used or not were associated with adverse cardiovascular events after PCI in patients with ACS, and the multivariable logistic model showed that age, carotid plaque, coronary Gensini score, LP(a), and whether aspirin was used or not were associated with adverse cardiovascular events after PCI in ACS patients. The Spearman correlation analysis showed a certain degree of correlation between LP(a) and LDL-C and between LDL-C and coronary Gensini score. The logistic predictive model for adverse cardiovascular events was logit (P) = 4.559 + 0.017 (age) + 0.311 (carotid plaque) + 0.010 (coronary Gensini score) + 0.004 (LP(a)) + 0.017 (LDL) + 0.674 (whether aspirin was used or not), which had an area under the ROC curve of 0.74 and a value of >0.05 based on the Hosmer-Lemeshow goodness-of-fit test. Conclusion The predictive model based on LP(a) and LDL-C has a good performance in predicting adverse cardiovascular events after PCI in ACS patients.