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Overgrazing is considered to be a key driver of undesired transition by the definition of rangeland State and Transition Models (STMs). Conceptually, the probability of moving to a less desirable state or community phase (i.e., Easily-reversible variants of states) increases with increased grazing pressure. Yet, how these probabilities change with the level of grazing is rarely known or estimated. Three blue grama (Bouteloua gracilis) study sites located on the Plains of Eastern New Mexico were monitored for 35 years, providing the data required to estimate the probability of broom snakeweed transition to different levels of infestation (None/Light, Moderate, Heavy). A stochastic Monte Carlo simulation model was developed which incorporates site-specific weather variability and stochastic events to estimate the net present value of income, considering the lease value of forage. Broom snakeweed, a short-lived perennial woody shrub, can quickly invade when environmental conditions are favorable and die out with drought. Using the long-term monitoring data and logistic regression it was determined that the probability of snakeweed invasion increased with higher April temperatures, with increased rainfall during the second quarter, and when a heavy stand of the invasive weed was present the previous fall. Further, as the amount of herbaceous grass material increased the probability of snakeweed infestation decreased. Recognizing that grazing reduces year-end herbaceous standing crop, snakeweed transition probabilities at various stocking rates were computed. If a successful snakeweed control treatment moved the weed infestation level to the None/Light category, treatment life was estimated to be 3.2 years with a 50% grazing use level, 4.1 years at 35% use, and 5.1 years with a conservative 20% use. Thus, light grazing was environmentally beneficial, but there was a tradeoff with economic returns. The estimated discounted net present value was $42, $71, and $96 for the 20%, 35% and 50% use rates, respectively.