With phishing emails being a major problem worldwide which is only getting larger by the year, there needs to exist solutions to combat them as they can cause tremendous harm to society. This research aims to compare numerous machine learning models and transformers for multilingual spam detection using English, French, and Russian emails. We evaluate the models using accuracy as two of the three experiments have nearly balanced test data. Our results show that, on average, XLM-Roberta performs the best out of all of the tested models in terms of accuracy.