The gas turbine endwall is bearing extreme thermal loads with the rapid increase of turbine inlet temperature. Therefore, the effective cooling of turbine endwalls is of vital importance for the safe operation of turbines. In the design of endwall cooling layouts, numerical simulations based on conjugate heat transfer (CHT) are drawing more attention as the component temperature can be predicted directly. However, the computation cost of high-fidelity (HF) CHT analysis can be high and even prohibitive especially when there are many cases to evaluate such as in the design optimization of cooling layout. In this study, we established a multi-fidelity (MF) framework in which the data of low-fidelity (LF) CHT analysis were incorporated to help the building of a model that predicts the result of HF simulation. Based upon this framework, MF design optimization of a validated numerical turbine endwall model was carried out. The high- and LF data were obtained from the computation of fine mesh and coarse mesh, respectively. In the optimization, the positions of the film cooling holes were parameterized and controlled by a shape function. With the help of MF modeling and sequentially evaluated designs, the cooling performance of the model endwall was improved efficiently.