Decision making under uncertainty involves making decisions in situations where there is no information concerning future events. To resolve this problem in optimal stocking control when the growth function of a species is initially unavailable and the decision maker is risk neutral, adaptive optimization can be used which utilizes the information generated in previous stages to transform the decision problem from the case of uncertainty to risk. At each stage, the growth function is revised by considering newly obtained growth data. The current stocking level which was determined in the latest optimization is used as the initial stocking level for a new optimization. The mean annual increment (MAI) of each stage is calculated, and the stage where the MAI culminates is the optimal rotation. The proposed model is applied to a hypothetical Douglas-fir stand as an illustration. The values of information are calculated from the MAI under certainty, risk, and uncertainty. Forest Sci. 30:921-927.