A linear statistic Fy is called linearly prediction sufficient, or shortly BLUP-sufficient, for the new observation y * , say, if there exists a matrix A such that AFy is the best linear unbiased predictor, BLUP, for y *. We review some properties of linear prediction sufficiency that have not been received much attention in the literature and provide some clarifying comments. In particular, we consider the best linear unbiased prediction of the error term related to y *. We also explore some interesting properties of mixed linear models including the connection between a particular extended linear model and its transformed version.