A heterogeneous flexible neural tree (FNT) for function approximation was proposed. FNT was studied under Pareto-based multiobjective genetic programming framework. A diversity-index was introduced to maintain diversity in genetic population. FNT was found competitive with other algorithm when cross validated over datasets. Evolutionary weighted ensemble of HFNTs further improved FNT performance.