In this article we propose a Bayesian regression model called the Bayesian generalized partial linear model which extends the generalized partial linear model. We consider Bayesian estimation and inference of parameters for the generalized partial linear model (GPLM) using some multivariate conjugate prior distributions under the square error loss function. We propose an algorithm for estimating the GPLM parameters using Bayesian theorem in more detail. Finally, comparisons are made between the GPLM estimators using Bayesian approach and the classical approach via a simulation study.