This study shows how applying compressed sensing (CS) to (19)F chemical shift imaging (CSI) makes highly accurate and reproducible reconstructions from undersampled datasets possible. The missing background signal in (19)F CSI provides the required sparsity needed for application of CS. Simulations were performed to test the influence of different CS-related parameters on reconstruction quality. To test the proposed method on a realistic signal distribution, the simulation results were validated by ex vivo experiments. Additionally, undersampled in vivo 3D CSI mouse datasets were successfully reconstructed using CS. The study results suggest that CS can be used to accurately and reproducibly reconstruct undersampled (19)F spectroscopic datasets. Thus, the scanning time of in vivo(19)F CSI experiments can be significantly reduced while preserving the ability to distinguish between different (19)F markers. The gain in scan time provides high flexibility in adjusting measurement parameters. These features make this technique a useful tool for multiple biological and medical applications.