We construct root-n consistent plug-in estimators for conditional expectations of the form E(h(X n+1 , . . . , X n+m )|X 1 , . . . , X n ) in invertible linear processes. More specifically, we prove a Bahadur type representation for such estimators, uniformly over certain classes of not necessarily bounded functions h. We obtain in particular a uniformly root-n consistent estimator for the m-dimensional conditional distribution function. The proof uses empirical process techniques.Keywords. Von Mises statistic, kernel smoothed empirical process, residual-based kernel density estimator, stochastic expansion, infinite-order moving average process, infinite-order autoregressive process.