A note about what is the output in predict.lm(lm_model, test_data, type=”terms”):

## first explain what is type="terms":  If type="terms" is selected, a matrix of predictions 
## on the additive scale is produced, each column giving the deviations from the overall mean 
## (of the original data's response, on the additive scale), which is given by the attribute "constant".
 
set.seed(9999)
x1=rnorm(10)
x2=rnorm(10)
y=rnorm(10)
lmm=lm(y~x1+x2)
predict(lmm, data=cbind(x1,x2,y), type="terms")  
 
lmm$coefficient[1]+lmm$coefficient[2]*x1+mean(lmm$coefficient[3]*x2)-mean(y)-predlm[,1]
lmm$coefficient[1]+lmm$coefficient[3]*x2+mean(lmm$coefficient[2]*x1)-mean(y)-predlm[,2]