Journal of Data Processing Vinita Malik, Sukhdip Singh 8 3 2018 https://doi.org/10.6025/jdp/2018/8/3/100-105 http://www.dline.info/jdp/fulltext/v8n3/jdpv8n3_3.pdf Various iterations of testing of the software are required for fulfilling specific quality parameters which further helps in quality management of any software. The heart of this research pumps for a Neuro Fuzzy Framework that will be utilized for mitigating software risks and such risk mitigation will lead to test case prioritization. This approach for risk mitigation has been considered due to high accuracy levels. Here the system will be trained by Bayesian regulation approach due to high prediction capabilities. Requirements identification has been done for the development of prototype of the tool which will determine risk levels. Once requirements are identified then by risk analysis the testing effort will be estimated properly for software quality improvement. The algorithmic paradigm has been developed for the proposed system which will be implemented by MATLAB or by Java Frameworks. Fuzzy logic has been employed to make fuzzy inference system.