High-fidelity modeling based on experiments or simulations is generally very expensive. Low-fidelity models, when available, typically have simplifying assumptions made during the development and hence are quick but not so accurate. We present development of a new and novel approach for multi-fidelity model fusion to achieve the accuracy of the expensive high-fidelity methods with the speed of the inaccurate low-fidelity models. The multi-fidelity fusion model and the associated uncertainties is achieved using a new derivation of the high dimensional model representation (HDMR) method. The method can provide valuable insights for efficient placement of the expensive high-fidelity simulations in the domain towards reducing the multi-fidelity model uncertainties. The method is applied and validated with aerodynamic and aerothermodynamic models for atmospheric re-entry.