Maximum likelihood estimates of the parameters in linear models with censored normal responses may be simply obtained using the EM algorithm. The iterative computations required for the regression coefficients are identical to those described by Schmee and Hahn for least squares estimates, but those for the variance estimates are different. The biases of the two variance estimates are discussed.