Traditional design of indoor airflow requires a designer to provide thermo-fluid boundary conditions to run a computational fluid dynamics (CFD) program in order to obtain the air distribution. If the air distribution does not satisfy the thermal comfort and indoor air quality criteria, the designer needs to change the boundary conditions until the design criteria are met. This design process can be time consuming while the final design may not be optimal. This study develops inverse design methods that use design objective, such as desired thermal comfort and indoor air quality, as design inputs. Then the methods can identify the required thermo-fluid boundary conditions to achieve the design objective. The inverse design methods include CFD-based adjoint method, genetic algorithm, etc. The applications of the methods to a complex airline cabin show that the inverse design methods are very promising as a future design tool.