The giant panda (Ailuropoda melanoleuca) is the most basal living species in the phylogeny of the family Ursidae, with a specialized diet composed of a variety of bamboo species. The evolutionary history and past distribution patterns of the giant panda remain poorly understood. Our aim was to integratively apply distinct methods to evaluate the evolutionary history and distributional patterns of the giant panda; these included phylogeography, ecological niche modeling (ENM), and fossil data. To this end, we characterized the panda's past and present ecological niches and the environmental conditions that define them. To estimate the panda's phylogeographic patterns and the environmental conditions (precipitation and temperature) available across its historical geographic range, we evaluated its past distribution during the Last Glacial Maximum (LGM). Considering that modeling biotic interactions (e.g., foraging, predation) is still an enormous challenge, we propose a novel modeling strategy based on the panda's specialized diet, using an ensemble of three bamboo genera with distribution across the panda's historical geographic range. Finally, we tested the accuracy of our approach by evaluating its ability to predict the LGM fossils. Our results support that the panda's diversification across its distribution happened ca. 2.7 million years (Mya), coinciding with the likely period when the panda changed from a carnivorous to a vegetarian diet (from the Pleistocene to the Pliocene), acquiring its exclusively bamboo-feeding habits until the mid-Holocene. Our findings provide evidence of a historical directional niche change along which the panda has currently reached the lower limits of temperature and precipitation conditions existing on the geography where its food is available. Our proposed ENM based on the panda's food habits accurately predicted 85.7% of the LGM fossils, in stark contrast with the traditional approach of modeling the distribution of species by using exclusively its own occurrences. These results provide insights on how to include Eltonian components to undertake more robust ENM when only abiotic variables are available. We emphasize the importance of integrating fossil information, whenever available, into the niche modeling process to include the historical component when estimating species ecological niches.