This paper sets out a general criterion for the identifiability of a statistical system, based on Kullback's information integral. It is shown that the general identification problem is equivalent to a maximisation problem, or where parameter restrictions are present, a problem in nonlinear programming. The relationship of this criterion to that based on the information matrix of the underlying distribution is also exhibited.