Puff pastry is characterized by a light and flaky texture due to its unique combination of fat and dough in a layered structure. Lamination and sheeting are steps applied to create multiple layers and a fixed thickness. The layered structure has to be continuous to promote desirable texture after baking. The aim of the present study is to apply imaging techniques and imaging analysis used for other food systems, to better understand the croissant-making process, in particular the development of its structures (layers and bubbles). In this work, confocal laser scanning microscopy (pixel size=0.6micrometerx0.6micrometer) is used to study puff pastry after sheeting. Calculations applied on CLSM image after thresholding and labeling of fat layers provide information about the thickness along each layer (fat and dough), the number of fat layers compared to the expected number, and the number of ruptures in fat layers. The effect of the number of sheets, decreasing the thickness of fat layers, on these parameters was analyzed. If image processing and analyzing are available on CLSM image of croissant, so CLSM in combination with image analysis could be an applicable tool for analyzing effect of process in industry. Global and local expansion during proving was monitored with magnetic resonance imaging (0.5mm×0.5mm) with lower spatial resolution than CLSM but compatible with a visualization of the whole product. Maps of gas, fat and dough proportions in each voxel were calculated from each image using a dedicate algorithm. This allowed to monitor the thickness of each dough layer as well as to evaluate their relative contribution to global expansion. The largest bubbles during proving were visualized and ruptures in fat layers were also visualized and discussed relative to the sensitivity threshold of the measurement method.