A file format identification system can predict file formats associated with binary data. The file format identification system can extract n-grams, such as byte 4-grams, from the binary data. A trained neural network with at least one embedding layer can generate embedding arrays that correspond to the extracted n-grams. A trained file format classifier can compare values in the embedding arrays with patterns of values associated with known file formats. The trained file format classifier can accordingly determine which of the known file formats are most likely to be associated with the binary data.