The competing risks model plays a pivotal role in the analysis of various domains, including engineering, econometrics, and biology. When a product being tested is likely to fail due to multiple factors, these factors conflict with each other to precipitate product failure. This situation is referred to as the competing risks problem. This paper specifically concentrates on a competing risks model that employs a generalized progressive hybrid type-II censoring scheme . It assumes that the underlying lifetime distributions of the failure causes follow Weibull distribution. The paper derives maximum likelihood estimates and Bayes estimates , utilizing Markov Chain Monte Carlo techniques for computing Bayes estimates and credible intervals. Further, Bayes estimates of the parameters which obtained based on squared error and linear exponential loss functions under the assumptions of independent Gamma priors. To illustrate these concepts, the paper includes simulation studies and real-world examples.