Summary: We consider maximum likelihood estimation for stochastic differential equations based on discrete observations when the likelihood function is unknown. A sequence of approximations to the likelihood function is derived, and convergence results for the sequence are proven. Estimation by means of the approximate likelihood functions is easy and very generally applicable. The performance of the suggested estimators is studied in two examples, and they are compared with other estimators.