In recent years, China’s bond market has achieved rapid development. At the same time, with the robust increase of bond offering, especially the growing offering of bonds without credit guarantee, the credit rating of corporate bonds changes at times and the downgrading of some corporate bonds did result in certain negative disturbance in the financial market. For this reason, more and more investors’ and supervisors’ attention has been focused on the credit risk of corporate bonds and the transitions of credit rating. How to predict the migration of credit rating is a central concern of investors and supervisors, and the most important point here is to find out the key indicators for such prediction. Current financial information may indicate the creditworthiness of an on-going firm because of its significant influence on the future performance of a firm. Current literature mainly focuses on foreign bond markets but in China, little discussion can be found in this aspect, not to mention systematic research. There are many differences between foreign bond markets and domestic bond markets, so whether the existing research conclusions based on foreign bond markets can be applied to Chinese markets deserves deep exploration. This paper tries to make an exploratory study on the financial indicators of credit rating transitions of Chinese corporate bonds with fixed-income and find out the key variables. By building the multinomial logistic regression model, the determinants of credit rating transition for corporate bonds with fixed-income are studied, and the empirical results are shown as follows: (1) Just like the conclusions of previous foreign studies, the results indicate that the current financial information may indicate the creditworthiness of an on-going firm because of its significant influence on the future performance of a firm. In addition, it appears that a relatively small number of independent variables could do a creditable job of predicting credit rating, the accuracy of which is between 51.2% to 64.3%. (2) The changes of both profitability ratios and solvency ratios may have statistically significant effects on the transition of credit rating. What deserves special attention is that downgrading and upgrading are sensitive to different financial ratios, which may be caused by the fact that the corporate bonds showing credit rating transitions have the characteristics of centralized maturity, concentrated industry and different fundraising objectives. . The changes of all the three solvency ratios in the negative direction may result in credit downgrading, among which the assets-liabilities ratio is the most important variable. On the other hand, among the three profitability ratios, only the reduction of main operation margins may lead to credit downgrading. By contrast, credit upgrading is mainly sensitive to profitability ratios. Enterprises with good profitability performance are more likely to achieve credit upgrading and firms with high ROTA and RONA will have a higher probability to achieve credit upgrading. (3) According to the empirical results of this study, the changes of operating capacity of the enterprise have statistically insignificant effects on credit rating transition. This result may be due to the limitation of data collection and there only one variable used to measure operating capacity. When more data is available, further analysis can be made. In sum, this paper has three main implications: (1) If issuer of corporate bonds wants to get a higher credit rating in the future, they should try to improve their profitability performance. (2) Portfolio risk managers may consider reducing the investment proportion of one bond or eliminate it from their portfolio to reduce credit risk if they see significantly negative changing of solvency performance of this issuer. (3) Supervisors need to pay attention to the negative changing of solvency performance and the profitability ratio of an issuer in order to conduct effective supervision. However, with the challenge of data collection, both the sample and the financial indicators under analysis are limited. Whether the empirical results could be generalized deserves further test when sufficient research conditions can be accessed. Further research can also take macroeconomic indicators into consideration to present more meaningful conclusions.