The rapid expansion of wind energy globally underscores its pivotal role in the global energy transition. However, wind farm wake losses, resulting from complex interactions between turbines, hinder the overall efficiency. The wake of a wind turbine, characterized by reduced wind speed and increased velocity fluctuations downstream, significantly impacts the wind farm performance due to interactions with the upstream turbines. Accurate modelling of these interactions is essential for designing efficient wind farms. This chapter provides details of two design-oriented analytical wake modelling frameworks, namely the top-down and bottom-up approaches. Top-down models focus on large wind farms and their interactions with the atmospheric boundary layer. In contrast, bottom-up models focus on the wakes of individual turbines and construct models for the entire wind farm using different wake-merging methods. Different variants on these broad themes are discussed. The performance of these models is compared to predictions obtained from high-fidelity large-eddy simulations. The efficacy of analytical wake models in reproducing the most important features of the flow field at a fraction of the cost is demonstrated.