This study empirically examines the liaison amid credit risk management and bank performance in a multivariate framework using bank size, non-performing loans, real GDP, net income, inflation and return of total assets to loans as indicators of credit risk and return of assets as a proxy of bank performance for some selected commercial banks in China from 2006-2017. With the application of panel econometric approaches that account for the issues of cross-sectional dependence and heterogeneity, results from the P-Y homogeneity test, Pesaran CD_LM test, CIPS panel unit root test, Pedroni and Durbin-Hausman panel cointegration, the AMG estimator and the DH panel Granger causality test show that: 1) the panel time series data are heterogeneous and cross-sectionally dependent; 2) analyzed variables are integrated are of the same order (I(1)); 3) there exists a structural long-run relationship amongst the analyzed variables; 4) non-performing loan has a mitigating impact on bank performance, whereas net income and bank size have positive effect on bank performance. Real GDP and inflation impact negatively on bank performance but insignificant whilst the ratio of total assets to loans on the other hand also has a statically insignificant but positive effect on bank performance; 5) a variety of causal relationships are identified amongst analyzed variables; 6) conclusions as well as policy implications are efficient and robust since this study utilizes econometric techniques addresses the issues of heterogeneity and cross-sectional dependence.