In histopathology, it is highly crucial to have chemical and structural information about tissues. Additionally, the segmentation of zones within a tissue plays a vital role in investigating the functions of these regions for better diagnosis and treatment. The placenta plays a vital role in embryonic and fetal development and in diagnosing some diseases associated with its dysfunction. This study provides a label-free approach to obtain the images of mature mouse placenta together with the chemical differences between the tissue compartments using Raman spectroscopy. To generate the Raman images, spectra of placental tissue were collected using a custom-built optical setup. The pre-processed spectra were analyzed using statistical and machine learning methods to acquire the Raman maps. We found that the placental regions called decidua and the labyrinth zone are biochemically distinct from the junctional zone. A histologist performed a comparison and evaluation of the Raman map with histological images of the placental tissue, and they were found to agree. The results of this study show that Raman spectroscopy offers the possibility of label-free monitoring of the placental tissue from mature mice while simultaneously revealing crucial structural information about the zones.