This document describes research investigating different classification methods to determine the best quality Portuguese white wines. It analyzes decision trees, logistic regression, multiple regression, and the k-nearest neighbors (KNN) algorithm. Initial trials found accuracy below 60% for decision trees, below 55% for logistic regression, and below 50% for multiple regression. The document then details implementing KNN in Matlab. After normalizing the data and setting k=1, it achieved over 99% accuracy in classifying wine quality. The KNN method with these optimizations was determined to be the most accurate classification approach.