Establishing protected area networks is a key strategy to reduce biodiversity loss and contributes to global conservation efforts. In the Philippines, where 240 protected areas have been designated and set aside for the conservation of biological diversity, approaches are needed to effectively conserve and manage these areas. Identifying High Conservation Value Areas (HCVA) is a practical approach to guide protected area managers for prioritising conservation action and monitoring conservation success. We applied the approach in seven sites (c. 555,000 ha) representing three major biogeographic regions of the Philippines National Integrated Protected Areas System. Using maximum entropy (MaxEnt) algorithm, we modeled species distributions from environmental predictors (e.g., topographic, bioclimatic, land cover, forest structure, and soil image layers) derived from remotely sensed data, and point occurrence data of species (comprised of birds, trees, mammals, amphibians, and reptiles) observed during field surveys in the selected protected areas. Species distributions from a total of 109 trigger species were modeled, and final species that fit the criteria were stacked to generate species richness maps for identifying HCVAs. Forest habitat change was delineated using official 2003 and 2010 national land cover maps that were generated from Landsat imagery. Results showed park boundaries that were inconsistent with areas of high species congruence. Forest habitat loss (c. 30,100 ha) was observed in all seven protected areas, mainly along forest edges and encroaching within park boundaries. Spatial analysis highlighted conservation hotspots where forest habitat loss threatened highly species-rich areas. The HCVA approach provided spatially explicit inputs for reformulating protected area management zones, setting measureable conservation targets, designing monitoring protocols, and establishing patrolling routes.