Summary Management of near-to-nature forests is frequently supplanted by faster-growing ‘industrial’ plantations on the basis of the latter’s superior economic return. These latter species often produce higher volumes of usable biomass in shorter periods of time. Increased yields come with a price, however. While some species provide a superior net present value, they may require a higher cash flow position on the part of the landowner. Other species may possess superior production capabilities but are susceptible to insect and disease attack. Under such conditions, less productive ‘native’ species might produce a satisfactory rate of return considering their reduced risk of attack. We examine two methods of evaluating differences in effective yield and rate of return. The first method, expected value analysis, is a deterministic method that uses decision tree methodology coupled with pre-determined probabilities of outcome for a given series of events and choices. The second method is a matrix model using stochastic transitions between healthy trees and different states of poor health. Markov processes are used to drive simulations of insect and disease attack, and then calculate net present value and optimal rotation age. We keep the final per-unit product price fixed to simplify the analysis and better validate the comparison between the deterministic and stochastic methods. We use longleaf (Pinus palustris Mill.), loblolly (P. taeda L.), shortleaf (P. echinata Mill.) and slash (P. elliottii Engelm.) pines as the species in our comparison. Longleaf is the slowest growing, but it is less prone to attack than the other three. Using more recent Forest Inventory and Analysis (FIA) data, both our Markov analysis and expected value analysis found loblolly and slash pines to be superior economic performers. Earlier FIA surveys support the selection of loblolly and slash over longleaf, but suggest that higher fusiform incidence might push the investment decision towards longleaf pine, particularly vis-a-vis slash pine at higher site indices. Both analysis methods provided the same outcomes, so long as they used the same data. Given this result, a decision tree methodology is a reasonable method for evaluating the economics of species choice in forest restoration activities.