Sea otters are well-known tool users, employing objects such as rocks or shells to break open invertebrate prey. We used a series of generalized linear mixed effect models (GLMEs) to examine observational data on prey capture and tool use from 211 tagged individuals from five geographically defined study areas throughout the sea otter’s range in California. Our best supported model was able to explain 75% of the variation in the frequency of tool-use by individual sea otters with only ecological and demographic variables. In one study area, where sea otter food resources were abundant, all individuals had similar diets focusing on preferred prey items and used tools at low to moderate frequencies (4-38% of prey captures). In the remaining areas, where sea otters were food-limited, individuals specialized on different subsets of the available prey and had a wider range of average tool-use frequency (0-98% of prey captures). The prevalence of difficult-to-access prey in individual diets was a major predictor of tool use, and increased the likelihood of using tools on prey that were not difficult to access as well. Age, sex, and feeding habitat also contributed to the probability of tool use, but to a smaller extent. We developed a conceptual model illustrating how food abundance, the prevalence of difficult-to-access prey, and individual diet specialization interacted to determine the likelihood that individual sea otters would use tools and considered the model’s relevance to other tool-using species. The dataset is a csv file of tool-use frequency based on observed foraging behaviors of tagged sea otters in California. Foraging data was collected opportunistically on each individual over time (typically 1-3 years). For each successful foraging dive, observers recorded the type of habitat the sea otter was using, the prey type consumed, and whether a tool use used to open the prey item. These observations are summarized as the percent prey captures with tool-use observed for each grouping of prey type, habitat type, and individual sea otter. Dataset also includes the age, sex, and general location of each individual. These data support the following publications: Ralls K, McInerney NR, Gagne RB, Ernest HB, Tinker MT, Fujii J, Maldonado J. 2017. Mitogenomes and relatedness do not predict frequency of tool-use by sea otters. Biology Letters 13(3). doi: 0.1098/rsbl.2016.0880 Fujii, JA, K Ralls, MT Tinker. 2017. Food abundance, prey morphology, and diet specialization influence individual sea otter tool use. Behavioral Ecology arx011. doi: 10.1093/beheco/arx011