政府和社会资本合作(PPP)模式步入规范实施阶段，存量项目提质增效与增量项目有序推进并举，民营企业参与活力提升，风险防控成为项目全生命周期管理的核心导向。在此背景下，以政府采购中的PPP工程建设企业为研究对象，该研究选取13项具有代表性的财务指标，构建“财务绩效分析—风险预测”研究框架，通过主成分分析(PCA)提取5个主成分因子作为企业财务实力的代理变量，再引入数据包络分析(DEA)开展财务绩效分析，最终结合主成分因子建立Logistic回归模型进行实证检验。结果表明，提取的5个主成分对PPP工程建设企业风险预测的准确率达90%,可通过企业财务实力有效预判其经营与财务风险；同时，DEA分析揭示了企业效率特征与财务风险的内在关联，为风险成因诊断提供了补充依据。研究有助于提高政府采购效率，为PPP工程建设项目的顺利建设、高效运营提供科学借鉴与参考。

At present, the Public-Private Partnership(PPP)model has entered a phase of standardized implementation, with the simultaneous advancement of quality improvement and efficiency enhancement of existing projects and the orderly development of new projects, further boosted vitality of private enterprises′ participation, and risk prevention and control serving as the core guiding principle for the whole-life-cycle management of projects.Against this backdrop, the present study takes PPP engineering and construction enterprises in government procurement as the research objects, selects 13 representative financial indicators, and establishes an integrated research framework of “financial performance analysis-risk prediction”,which involves three sequential steps: first, extracting five principal component factors as proxy variables for enterprises′ financial strength by means of Principal Component Analysis(PCA);second, introducing Data Envelopment Analysis(DEA)to conduct financial performance analysis; and finally, constructing a Logistic regression model combined with the principal component factors for empirical testing.The results show that the five extracted principal components achieve a 90% accuracy rate in predicting the risks of PPP engineering and construction enterprises, enabling the effective pre-judgement of their operational and financial risks based on financial strength, while DEA analysis reveals the intrinsic correlation between enterprise efficiency characteristics and financial risks, thus providing supplementary evidence for diagnosing the causes of risks.The research findings help improve the efficiency of government procurement and offer scientific references for the smooth construction and efficient operation of PPP engineering projects.