The concepts of “integrated control” and “integrated pest management” (IPM) were devised by entomologists, but they proved relevant to the monitoring and control of virtually any agricultural pest (i.e., weeds, fungi, vertebrates). Within IPM, economic threshold characterized pest densities that would have negative impacts and economic injury level characterized amounts of predicted crop injury (destruction) that would allow recovery of potential pest-control costs. Approximately 150 species or groups of vertebrates have been documented to pose human health/safety risks or to cause agricultural, natural resource, and property losses in North America. Rodent (e.g., mice, rats, ground squirrels) and bird (e.g., blackbirds, gulls, cormorants) populations are the most frequently cited species/groups of vertebrates linked with IPM. Uncertainty characterizes IPM applications to control damage by these species/groups. Uncertainty is a measure of variance, which occurs due to the myriad of biological, crop, economic, meteorological, pesticide, production, seasonal, and soil unknowns that impact IPM programs. Six uncertainty-reduction techniques are commonly used by economists: 1) worst-/best-case scenario, 2) contrived scenarios, 3) decision tree analysis, 4) sensitivity analysis, 5) Monte Carlo simulation, and 6) systematic projections. This paper reviews key IPM literature, especially economic literature, and discusses techniques that can reduce the economic uncertainty of using IPM programs with vertebrates.