This research introduces an innovative traffic classification method tailored for 5G networks. The approach leverages deep transfer learning by utilizing pre-trained models and fine-tuning them. We evaluate several deep-learning models in a transfer learning setting. The Inception model being identified as the top-performing model shows an improvement of approximately 10% in terms of F1-score between IDS-based DTL and the same scheme without DTL.