Expected runout distances and related return periods are the most important parameters needed for zoning in terrain prone to snow avalanching. Hazard mapping procedures usually allocate areas of land to zones with a different degree of danger based on return periods estimated for given snow volumes in the starting zone or with statistical/dynamical models. On forested avalanche paths, dendrogeomorphology has a great potential to add critical input data to these calculations in terms of recurrence intervals or return periods. However, quite paradoxically, recurrence interval maps of snow avalanches have only rarely been retrieved from tree-ring analysis and mostly represent the inverse of the mean frequency of avalanches that could be retrieved locally rather than the return period. The purpose of this study therefore was to propose a consistent approach for tree-ring based recurrence interval mapping of snow avalanche events. On the basis of 71 snow avalanches retrieved from 2570 GD growth disturbances identified in 307 larch trees from three avalanche paths located in the vicinity of Täsch (Canton of Valais, Swiss Alps), we first followed the classical approach used in dendrogeomorphology and derived recurrence interval maps through interpolation from recurrence intervals observed at the level of individual trees. We then applied an expert delineation of the spatial extent of past events based on the location of disturbed trees. Our results show that the second step improved representation of expected patterns of recurrence intervals that typically increase as one moves down the centerline of the avalanche path. Despite remaining limitations and uncertainties precluding from direct use of our maps for hazard mapping purpose, these results suggest that dendrogeomorphic time series of snow avalanches can yield valuable information for the assessment of recurrence intervals of avalanches on forested paths for which only very limited or no historical data exists, and that this data can be obtained independently from meteorological data or numerical modeling.