In　risk　management,　we　often　assess　the　credit　risk　for　companies;　especially　study　the　default　risk　for　companies　with　a　high　liability-to-asset　rate.　In　this　paper,　logistic　regression　model　is　used　to　assess　the　listed　companies＇　credit　risk.　Selecting　listed　companies＇　63　financial　indicators　reflecting　companies＇　credit　characteristics　as　initial　independent　variables,　we　establish　logistic　regression　model　based　on　case-control　data.　We　also　determine　financial　indicators　measuring　listed　companies＇　credit　risk　by　hypothesis　testing　and　factor　analysis,　and　establish　logistic　regression　model　based　on　case-control　data　by　changing　different　sample　proportion　of　ST　companies　and　non-ST　companies.　Finally,　we　can　get　the　conclusion　that　predicted　accuracy　for　logistic　regression　model　based　on　case-control　data　with　sample　proportion　1:1;　1:2　is　high.　For　risk　assessment,　it　is　an　effective　method　to　establish　logistic　regression　model　based　on　case-control　data.　It　is　more　practical　and　the　probability　of　committing　Type　I　error　or　Type　II　error　is　also　low.