Adding more trees reduces a forest’s simulation noise, but dependence between trees leaves another source of uncertainty. This work develops a design-based account of random-forest variance and examines how observation reuse and the alignment of tree partitions contribute to it. It also develops procedure-aligned synthetic resampling for estimating uncertainty.