The purpose of this study is to investigate the effects of five different balanced incomplete block on test equating using the 3 parameter logistic model in BILOG-MG. The impacts of two factors will be discussed: 1. the number of sample, 2. the distributions of ability. The result shows that the best decision of using balanced incomplete block is sample size exceed 5460 and the distribution of ability is normal or two- kurtosis. When distribution of ability is normal or two-kurtosis distribution, it has good equating effect using balanced incomplete block designs.