The giant panda (Ailuropoda melanoleuca), is one of the world’s most endangered species. Habitat loss and fragmentation have reduced its numbers, shrunk its distribution, and separated the population into isolated subpopulations. Such isolated, small populations are in danger of extinction due to random demographic factors and inbreeding. We used least-cost modeling as a systematic approach to incorporate satellite imagery and data on ecological and behavioral parameters of the giant panda collected during more than 10 years of field research to design a conservation landscape for giant pandas in the Minshan Mountains. We identified 8 core habitats and 4 potential linkages that would link core habitats CH3, CH4, and CH5 with core habitats CH6, CH7, and CH8. Establishing and integrating the identified habitats with existing reserves would create an efficient reserve network for giant panda conservation. The core habitats had an average density of 4.9 pandas/100 km2 and contained approximately 76.6% of the giant panda population. About 45% of the core habitat (3245.4 km2) existed outside the current nature reserves network. Total estimated core habitat decreased between 30.4 and 44.5% with the addition of residential areas and road networks factored into the model. A conservation area for giant panda in the Minshan Mountains should aim to ensure habitat retention and connectivity, improve dispersal potential of corridors, and maintain the evolutionary potential of giant pandas in the face of future environmental changes.