If we are given a document and an author's profile, can we determine if this author published the document? This problem is known as authorship verification. The task of identifying an author's work through the use of stylometry has been around for hundreds of years. Today, analysis of this kind falls under the large field of forensic science. Much like a fingerprint, writing samples from an author can be used to identify characteristics of the writer and ultimately identify who wrote a work. The process of building a profile about an author's writing style is called stylometry. However, using the profiles of an author to distinguish one author's work from another author's work is challenging due the large amount of noisy data. Advances in natural language processing and artificial intelligence have given researchers and practitioners new techniques for extracting and identifying patterns in this data. Ultimately, these techniques will allow us to verify or eliminate the author of a given work.In this work, we are proposing a solution to the authorship verification problem using a supervised feedforward neural network.