The sample size determination plays a significant role in design and analysis of many engineering problems plus data sampling projects. There is a number of sampling techniques including both classical as well as Bayesian techniques and only some of them consider the economical aspect. The objective of this paper is to offer an economic Bayesian approach for determination of sample size. Mathematical models are derived and used to establish implementation boundaries from economic and technical viewpoints. In addition, numerical examples are used to highlight the economic advantages of Bayesian approach. Using simulated data, the performance of the proposed approach is compared to the classical methods in terms of the number of sample size criterion.