In this paper the problem of treatment allocation is studied from the predictive decision theoretical point of view. The utility of obtaining some final characteristics y when a treatment a is applied to a person with initial facet x is assumed to be known. The problem is then reduced to the derivation of the expected utility of a given x, by means of either prognostic or diagnostic distributions.
To find prognostic distributions, regression models and appropriate partitions of the population, according to some initial and/or special facets, are used. This paper proposes some criteria for designing experiments, in order to take the best advantage of the available information and the sample size. The methods proposed have practical interest when the final facets are continuous