Various sensors and analytic tools have been developed to assist with the collection and analysis of data regarding the activities of animals at pasture. We tested an accelerometry-based activity monitor, the Kenz Lifecorder EX (LCEX; Suzuken Co Ltd, Nagoya, Japan), to differentiate between foraging and other activities of beef cows in a steeply sloping pasture. Logistic regression (LR) and linear discriminant analysis (LDA), two of the most widely used techniques for distinguishing animal activities based on sensing device information, were employed in the analysis. An LCEX device was worn on a collar by each of four cattle over the course of 4 d, during which time the activity (foraging, resting, ruminating, walking, and grooming) of each cow was recorded by trained observers at 1-min intervals for a total of 15 h. LR and LDA were applied to the LCEX and observer data to distinguish between foraging and other activities. Overall, a more accurate measure was obtained by LDA (90.6% to 94.6% correct discrimination among cows) than by LR (80.8% to 91.8% correct discrimination). The threshold LCEX value for distinguishing between foraging and other activities varied among cows, and the correct discrimination rate for the pooled data set was 92.4% for LDA and 85.6% for LR. Based on individual cow LDA, the time spent foraging averaged between 443 and 475 min · d⁻¹. Our results indicated that LCEX can be used to identify the foraging activity of cattle.