Time-accurate solutions of the Euler or Navier-Stokes equations are still nowadays a computationally expensive approach for applications where a magnitude of parameters has to be investigated. This work focuses on flight dynamics-related studies. The generation of several low-order models for the evaluation of unsteady and non-linear aerodynamic loads are investigated. The validity of low-order models presented is assessed by comparing the model output with unsteady time-accurate Computational Fluid-Dynamics (CFD) simulations. The test case is the NACA 0012 airfoil. The low-order models considered are: a non-linear model based on aerodynamic derivatives, a Volterra model, a surrogate-based recurrence-framework model, linear indicial functions and radial basis functions trained with neural networks.