A great challenge for ecologists is predicting how communities in fragmented tropical landscapes will change in the future. Available evidence suggests that fragmented tropical tree communities are progressing along a trajectory of ‘retrogressive succession’, in which the community shifts towards an early or mid-successional state that will persist indefinitely. Here, we investigate the potential endpoint of retrogressive succession, examining whether it will eventually lead to the highly depauperate communities that characterise recently abandoned agricultural lands. We tested this hypothesis by using neural networks to construct an empirical model of Amazonian rainforest-tree-community responses to experimental habitat fragmentation. The strongest predictor of tree-community composition in the future was its composition in the present, modified by variables like the composition of the surrounding habitat matrix and distance to forest edge. We extrapolated network predictions over a 100 yr period and quantified trajectories of forest communities in multidimensional ordination space. We found no evidence that forest communities, including those near forest edges, were converging strongly towards a composition dominated by just one or two early successional genera. Retrogressive succession may well be stronger in fragmented landscapes altered by chronic disturbances, such as edge-related fires, selective logging, or intense windstorms, but in this experimental landscape in which other human disturbances are very limited, it is unlikely that forest edge communities will fully revert to the species poor assemblages observed in very early successional landscapes.