Gas turbine engines are conceptually designed using performance maps that describe the compressor’s effect on the cycle. During the traditional design process, the cycle designer selects a compressor design point based on criteria to meet cycle design point requirements, and performance maps are found or created for off-design analysis that meet this design point selection. Although the maps always have a pedigree to an existing compressor design, oftentimes these maps are scaled to account for design or technology changes. Scaling practices disconnect the maps from the geometry and flow associated with the reference compressor, or the design parameters which are needed for compressor preliminary design. A goal in gas turbine engine research is to bridge this disconnect in order to produce acceptable performance maps that are coupled with compressor design parameters. A new compressor conceptual design and performance prediction method has been developed which will couple performance maps to conceptual design parameters. This method will adapt and combine the key elements of compressor conceptual design with multiple-meanline analysis, allowing for a map of optimal performance that is attached to reasonable design parameters to be defined for cycle design. This method is prompted by the development of multi-fidelity (zooming) analysis capabilities, which allow compressor analysis to be incorporated into cycle analysis. Integrating compressor conceptual design and map generation into cycle analysis will allow for more realistic decisions to be made sooner, which will reduce the time and cost used for design iterations.