Taking indebted ST listed companies and twice as many the non -ST of Shanghai and Shenzhen A -share from 2010 to 2012 as sample , the paper divides the sample into different kinds according to industry characteristics . Then we select 30 financial indica-tors that can reflect the business profitability , profitability of shareholders , cash flow capacity , operational capacity , development capacity and debt solvency . Finally , a Logit model based on principal component analysis method is proposed to analyze the predictive performance of the model for default probabilities and distinguish accuracy in different industries . The results show that there were significant differences and common features in default probabilities and distinguish accuracy of different industries .%以2010～2012年期间我国沪深A股因财务困境陷入ST的公司和按照1∶2比例配比的正常公司作为研究对象，并根据行业特点对样本进行划分。同时，选取能够反映企业盈利能力、股东获利能力、现金流量能力、营运能力、发展能力、偿债能力的30个财务指标，在主成分分析的基础上构建各年度的Logit模型，对各行业的违约概率和判别准确度分别进行分析。结果表明，不同行业的违约概率和判别准确度均存在显著差异且存在共性特征。
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