A normal semiparametric mixture regression model is proposed for longitudinal data. The proposed model contains one smooth term and a set of possible linear predictors. Model terms are estimated using the penalized likelihood method with the EM-algorithm. A computationally feasible alternative method that provides an approximate solution is also introduced. Simulation experiments and real data example are used to illustrate the methods.