This paper presents a solution on how to classify the fonts in the 17th century Romanian Cyrillic documents. This solution is based on a mix of unsupervised and supervised machine learning technics. The unsupervised process is the application of K-Means method to create the dataset with the fonts characters and their labels, whilst the supervised process is to train two different architectures of neural networks to classify these characters.