Estimating plant biomass in rangeland ecosystems is essential to understanding carbon cycling, impacts on natural resources, and ecological functioning or structure—all of which inform sustainable land management. However, biomass estimation has been relatively understudied for the sagebrush steppe of North America, one of the continent's most widespread ecosystems. As a nondestructive alternative to direct biomass measurements, allometric models may be used to estimate aboveground plant biomass using predictor variables once models are developed. With this as our aim, we developed species-specific and multispecies models for eight common bunchgrass species in Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle & Young) plant communities. As codominant perennials, these bunchgrass species provide much of the forage for large herbivores while contributing to soil stability and carbon storage. To develop allometric models for these bunchgrass species, we used individual height, basal diameter, and tiller count as predictor variables. On average, multiple-predictor models (RMSE CV = 61%) were more effective (i.e., exhibited more agreement between predicted and actual biomass) than single-predictor models (RMSE CV = 79%). Power models (RMSE CV = 66%) were slightly more effective than exponential models (RMSE CV = 72%). Applying models to each species demonstrated that the effectiveness of multispecies (RMSE CV = 65%) versus species-specific (RMSE CV = 67%) models largely depended on the species being modeled. Combining our models with plant density resulted in an area-based biomass estimate range (2.3–26.7 g/m2) that generally agreed with previous studies (0.2–19 g/m2). It is our hope that the allometric models developed in this study will be tested on various locations and ultimately inform rangeland management throughout the big sagebrush region.