Normalizing flows are a probabilistic method to estimate the underlying density of data samples. The method is flow based and non-parametric, with the aim of being flexible, but still computationally manageable. This report aims to explain the process of normalizing flows by the underlying principles of this probabilistic method. Both the method itself and the underlying principles are explained and reduced. An example of a normalizing flow is then implemented to showcase the method and support the underlying principles.