Abstract--Reliability is one of the quantifiable quality features of the software. Software reliability growth models (SRGMs) are used to assess the reliability achieve at different test times based on statistical learning models. Conventional time based SRGMS may not be accurate enough in all situations and such models cannot identify errors in small and medium sized applications. Numerous traditional reliability measures are used to test software errors during application development and testing. In the software testing and maintenance phase, however, new errors are taken into account in real time in order to determine the reliability estimate. In this article, we suggest using the Weibull model as a computational approach to solving the problem of software reliability modeling. In the anticipated model, a new distribution model is projected to develop the reliability estimation method. We compute the model developed and balance its presentation through additional popular software reliability increase models commencing the literature. Our test consequences demonstrate that the planned Model is greater to S-shaped Yamada, comprehensive Poisson, NHPP.