We measured twig basal diameters, diameters at point of browsing, and diameters of unbrowsed twig tips on 6 shrub species to estimate browse use without developing regression equations or relying upon before and after browsing measurements. Simulated browsing of twigs was predicted accurately for paper birch (Betula papyrifera), red-osier dogwood (Cornus stolonifera), prickly rose (Rosa acicularis), and Scouler's willow (Salix scouleriana). The technique adequately predicted leaf use only for Douglas maple (Acer glabrum). Minimum sample sizes to estimate total browsing of twigs appear feasible, if maximum error is expressed as percentage points around average use, rather than as percentage of average use. J. WILDL. MANAGE. 54(1):175-179 Inventory programs to estimate browsing by wildlife and livestock pose complex problems because of highly variable plant physiognomy, life history, and spatial distribution of browse species (Telfer 1981). Sampling methods range from visual assessments of shrubs use (e.g., Aldous 1944, Walmsley et al. 1980:191-194) to detailed clip-and-weigh determinations of current annual growth (CAG) or standing crop remaining in browsed compared to unbrowsed areas (Rutherford 1979). These techniques all possess inherent strengths and weaknesses depending on specific inventory objectives (Rutherford 1979, Telfer 1981, Pitt and Schwab 1988). Visual estimates offer an inexpensive and relatively easy method to assess shrub use, but are hindered by observer and statistical bias (Pechanec and Pickford 1937, Jolly 1954) and often fail to provide management agencies with verifiable levels of statistical confidence and precision. Clip-and-weigh techniques are typically expensive and tedious (Lyon 1970) and are more appropriate for intensive research than for extensive browse inventory programs (Rutherford 1979, Pitt and Schwab 1988); consequently, many compromises between visual estimates and total collection of available browse have been recommended for estimating shrub use (e.g., Shafer 1963, Halls et al. 1970). A technique commonly used to estimate browsing use is to regress twig biomass on shrub dimensions. Telfer (1969) produced generally high coefficients of determination between biomass and diameter at point of browsing for 38 shrub species and recommended that such predictive relationships be combined with twig counts to evaluate shrub use by comparing browsed and unbrowsed paired plots. Regression equations can also produce considerable savings in time, as Provenza and Urness (1981) required only 7 man-days to develop regression equations to estimate browsing use by goats, compared to 28 man-days for direct measurements of twig lengths before and after goat browsing. Other workers have produced similarly high correlations among shrub dimensions, browse production, and browse use, but cautioned that predictive equations may be highly variable depending on (1) time of year the twigs are collected (Potvin 1981), (2) geographical location (Basile and Hutchings 1966), (3) site conditions at time of sampling (Peek et al. 1971), (4) portion of shrub crown from which the sample is collected (Lyon 1970), and (5) age of twig (Telfer 1969). For example, Peek et al. (1971) regressed twig weight on diameter at point of browsing for 8 shrub species on 7 sites and reported that twig weights derived from a common equation differed from site-specific equations by more than 20% in 25 of 44 cases. They concluded that variations in overstory canopy closure, browsing intensity, and soil moisture produced sufficient variation in twig diameter relationships to preclude use of a common predictor equation of twig weight based upon twig diameter. Moreover, regressions of biomass on shrub dimensions to estimate browsing use usually required before and after browsing measurements (Lyon 1970). Jensen and Urness (1981) proposed an alternative technique for evaluating shrub use that