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Description: The FFMQ is a popular self-report instrument for mindfulness assessment. However, several studies report mixed evidence regarding its reliability and validity. In a recent replication study (Lecuona, García-Garzón, García-Rubio, & Rodríguez-Carvajal, 2019) several issues regarding its latent structure were found. Nevertheless, although only regarding to the inclusion of method factors, the Observe facet and whether the general mindfulness factor is from a second-order or a bifactor solution, thus facets where replicated successfully. This study proposes an exploratory approach for the FFMQ on an item level. Two open access samples were merged as a composite sample (total N = 1008). Regularized partial correlation networks were applied to freely explore relations between items. Latent dimensions were proposed with three approaches: Firstly, an a priori approach labeling theoretical item solutions for each facet in the network. Secondly, an exploratory graph analysis (EGA) was applied to estimate an empirically optimal solution. Thirdly, a modified EGA was applied to compare estimation methods. Network analysis showed a generally positive correlated network. While the theoretical solutions seem to fit, EGA and modified EGA proposed a 4-facet (merging Observe and Non-Judge) and 6-facet (splitting Actaware in two) solutions, respectively. We propose the 6-facet solution as the theoretically and empirically best solution for this data, since the theoretical 5-facet solution is not proposed by EGA, but the 4-facet solution is theoretically unstable. We also propose guidelines for researchers and applied uses of the FFMQ and cautionary warnings towards using the FFMQ.