Assessment of beef cow energy balance and efficiency in grazing-extensive rangelands has occurred on a nominal basis over short time intervals and has not accounted for the complexity of metabolic and digestive responses; behavioral adaptations to climatic, terrain, and vegetation variables; and documentation of the effects of nutrient form and supply to grazing cattle. Previous research using pen-fed cows demonstrated differences (P < 0.01) in efficiency of weight change ranging from 135 to 58 g/Mcal ME intake. Furthermore, variation in efficiency of ME use for tissue energy gain or loss ranged from 36% to 80%. In general, energy costs for maintenance, tissue accretion, and mobilization were greatest in Angus-based cows, intermediate in Brahmanand Hereford-based cows, and least in dairy-based cows. The most efficient cattle may reflect the types that are successful in semiarid grazing environments with low input management. Successful range cattle systems are likely the result of retention of animals that best adapted to the grazing environment and thus were potentially more efficient. Animals exposed to a variety of stressors may continually adapt, so energy expenditure is reduced and may tend to depart from the modeled beef cow in the 1996 NRC Beef Cattle Requirements. Critical factors comprising cow lifetime achievement, including reproductive success, disease resistance, and calf weaning weight, may be driven by cow total energy utilization in energy-limiting environments. Therefore, energy adjustments for adapted cattle within these landscapes and seasonal BW changes can alter seasonal NE m requirements. Evaluated studies indicate that in static grazing environments, NRC prediction fitness was improved compared with predictions from dynamic systems where cattle were influenced less by management and more by environmental conditions. Preliminary herd analyses cast doubt on the accuracy of NRC BCS descriptions representing NE m requirements of adapted females utilizing semiarid rangelands. Possible gaps are proposed that could be the basis for prediction inaccuracies. A more complete understanding of mechanisms contributing to productivity in the field than the current model predicts will improve future models to better simulate energetic accountability and subsequent female performance.