The Canton of Geneva is currently working on defining and mapping its green infrastructure (GI), in order to implement its biodiversity protection directives by 2030. Ecological connectivity is considered in the definition of the GI, as it is a key factor in managing the species extinction risk. It is considered a vital aspect of the landscape, because it can indicate how landscape facilitates or influences wildlife movement. In order to assess connectivity, animal movement data is essential as it provides precise behavioral information on the movements of organisms. Unfortunately, this kind of data is often missing or available only at local scales. Ecologists therefore must deal with a lack of data when trying to supply useful spatially explicit ecological models for conservation planning. To help managers in their efforts to define the GI, an alternative is to rely on local expert knowledge. We have thus applied a structured analytical framework to parameterize an ecological connectivity model combining expert opinion with three of the most used methods to assess ecological connectivity: graph theory, circuit theory and cumulative costs algorithm. By considering a selection of focal species representative of the different ecological requirements and movement behaviour of the regional wildlife, maps of priority areas for the promotion of ecological connectivity were obtained for red deer, roe deer, brown hare and common toad. We estimated the principal cross-border corridors at the scale of the Greater Geneva region, between France and Switzerland. Three transboundary high priority areas were highlighted in our maps. The localization of these areas is principally characterized by natural habitats such as forests, grasslands and freshwater ecosystems, but depends also on the agricultural areas. The principal natural barrier to animal movement is Lake Geneva, and the principal human barriers to movement are human settlements and highways that impede the regional displacements for all of the species. Considering the highways, the barrier effect could be diminished thanks to the recent construction of wildlife overpasses. We have seen that a close collaboration between local experts and ecological modelers is necessary when interpreting the conservation value of land potentially capable of promoting wildlife ecological connectivity. When implementing the GI, it will be useful to combine our models with field campaigns to measure the real functionality of the estimated priority areas, in order to guarantee the success of conservation actions.