A multivariate discrimination technique was established based on the Bayesian theory. Using this technique, P/S ratios of different types (e.g., Pn/Sn, Pn/Lg, Pg/Sn or Pg/Lg) measured within different frequency bands and from different stations were combined together to discriminate seismic events in Central Asia. Major advantages of the Bayesian approach are that the probability to be an explosion for any unknown event can be directly calculated given the measurements of a group of discriminants, and at the same time correlations among these discriminants can be fully taken into account. It was proved theoretically that the Bayesian technique would be optimal and its discriminating performance would be better than that of any individual discriminant as well as better than that yielded by the linear combination approach ignoring correlations among discriminants. This conclusion was also validated in this paper by applying the Bayesian approach to the above-mentioned observed data. A multivariate discrimination technique was established based on the Bayesian theory. Using this technique, P / S ratios of different types (eg, Pn / Sn, Pn / Lg, Pg / Sn or Pg / Lg) measured within different frequency bands and from different stations are combined together to discriminate seismic events in Central Asia. Major advantages of the Bayesian approach are that the probability to be an explosion for any unknown event can be directly calculated given the measurements of a group of discriminants, and at the same time correlations among These discriminants can be fully taken into account. It was proved theoretically that the Bayesian technique would be optimal and its discriminating performance would be better than that of any individual discriminant as well as better than that yielded by the linear combination approach ignoring correlations among discriminants. This conclusion was also validated in this paper by applying the Bayesian approach to the above-referred observed data.