In today's environment of intense competition, volatile economic conditions, rising default rates and increasing levels of consumer and commercial debt, an organizations ability to effectively monitor and manage its credit risk could mean the difference between success and failure. Consistent stream of failures and scandals in the banking and financial services industry have served as a catalyst for anxiety about risk. The risk anxiety generated by these events has led to the proliferation of new categories of risk and new models for managing these risks. The general objective of this study was to establish the influence of credit risk management practices on financial performance of commercial banks in Meru Town. The study covered all commercial banks which had been registered by the Meru County Government to operate in Meru Town by January 2018. Meru Town is the commercial hub for Meru County and all banks in the county have a presence in the town. The study concentrated on credit staff alone since they are the drivers of credit lending in banking industry. The study adopted a descriptive research design, which involves fact finding and enquiries of different types. The total population was 60 credit staff drawn from respective commercial banks. The study adopted a census because the population was not large, and there were well-organized structures where the respondents could be easily reached. A pilot study was carried out to ascertain validity and reliability of the data collection instrument - questionnaire. It Six credit managers from commercial banks in the neighbouring Nkubu Town, also located in Meru County, were issued with questionnaires through the test-retest approach. In the actual data collection, drop- and-pick method was used, after appointments had been booked with the respondents. Frequencies and percentages were used to analyse data and hypotheses were tested using Chi-Square. The analysed data was presented using frequency tables. The study established a relationship between financial performance and three of the variables namely, credit risk identification, measurement and monitoring. However, there was no adequate evidence to establish such a relationship with credit risk control as indicated by the chi-square test. It was concluded that credit management should focus more on credit risk identification, measurement and monitoring. The study recommended that commercial banks should continuously review and update their credit risk identification systems and strategies; that these financial institutions should invent models that measure credit risk accurately; that credit staff should undergo regular trainings on credit monitoring, and that terms and conditions of borrowing should be simplified to encourage uptake of credit. The findings of this study are likely to be of immense benefit to various stakeholders in the banking industry, including shareholders, managers, credit staff, borrowers, the government and the academic community