and evaluated mainly physico-chemical properties. In the present study, several biological indices were applied to determine whether biological indices could provide a more comprehensive understanding in terms of soil quality assessment in urban forests. Microbe and invertebrate biological indices (i.e. biodiversity of both microbe and invertebrate, enzyme activity of microbe, feeding activity of invertebrate) were examined at 6 urban forests with different levels of disturbance in Seoul, Korea. The results showed that feeding activity and biodiversity were significantly and positively intercorrelated, but not with the enzyme activity. We also examined whether these biological indices could be modeled as functions of soil physico-chemical characteristics. To develop a predictive model, we applied principal component regression. The results showed that first principal component represented more than 33% of the total variance of biological indices and gave a good relationship with soil physico-chemical characteristics (R2=0.71). The predictive model developed in this study can be used for qualitative but not for quantitative assessment of soil quality.