This paper is concerned with prediction in the spatial linear model using the maximum likelihood estimation of parameters in this model. In particular, we give some properties of predictors obtained on substituting the maximum likelihood estimators of model parameters into the form of the best-in the sense of minimum mean square prediction error-predictor. Such predictors are not optimal but we show them to be asymptotically equivalent to the optimum. We discuss practical aspects of this work and conclude by considering the connection with other areas.