Hedgerow intercropping system using Eucalyptus deglupta is an essential option for smallholder agroforestry farms for the reason that they amalgamate timber and food production.  Matching tree species to appropriate site conditions and stand management is vital for sound agroforestry timber production.  In this study, the multiple linear regression analysis was used to develop an appropriate prediction models for estimating yield, biomass expansion factor and future climate impact from soil chemical properties, physiographic characteristics, stand attributes, rainfall, temperature, biomass inventoried volume of bagras planted in hedgerow intercropping agroforestry system.  Results showed strong association of independent variables with the dependent variable based on the output of multiple regression analysis in all site index, yield prediction and biomass expansion factor models.  It was found that about 96.20% proportion of variance of yield can be predicted from site index, age, basal area and rainfall.  Comparison of yield and aboveground biomass accumulated by bagras from alley cropping and other agroforestry systems was in order woodlot > boundary planting > alley cropping.  Rainfall in this model also posed considerable influence in volume (2.8 % per 100 mm increase). The yield of bagras was negatively affected by the changes in future climate.  Yield will decrease linearly with seasonal mean rainfall and in 2050 volume will be reduced to an approximate amount of 0.0190 m3 (8 bd ft) per tree.