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ABSTRACT Lithium (Li) is classified as a critical raw material by many countries and is an essential component of Li‐ion batteries that underpin many fossil‐free technologies. This study reports the integrated use of petrophysical data, 3D geophysical inversion modelling and geological observations for the Järkvissle Li pegmatite field and surrounding area in central Sweden. The work aims to better constrain geological controls on Li pegmatite mineralization, the geophysical signatures of the mineralization and host meta‐supracrustal rocks and their 3D spatial distribution at depth. For the first time in Europe, the combined results of 3D inversions of airborne magnetic field data, very low frequency data, ground gravity data and resistivity models from laterally constrained 1D inversion of airborne Slingram measurements are integrated to characterize known Li pegmatite mineralization. It is done from a combined geological–geophysical perspective, with the aim to identify additional areas potentially favourable for Li pegmatites. At Järkvissle, Paleoproterozoic Li pegmatite mineralization occurs within a narrow deformation zone that is characterized by relatively high magnetic susceptibility (0.01–0.3 SI units), low resistivity (<2000 Ω m) and low rock density contrasts (<50 kg/m 3 ) down to ca. 600 m, reflecting a combination of structural and host rock characteristics. Regional airborne radiometric data (K, U and Th) lack corresponding anomalies, although based on ground spectrometry measurements pegmatites show marginally lower Th/K and higher U/K values relative to surrounding granites and meta‐supracrustal rocks. Petrophysical data for both Li‐enriched and common pegmatites indicate overall lower magnetic susceptibility (<ca. 5 × 10 −5 SI units) and density values (<ca. 2700 kg/m 3 ) compared to the host rocks, indicative of their fractionated and felsic compositions. 3D geophysical modelling, which incorporates inversion of ground gravity data, shows positive density contrasts (50–500 kg/m 3 ) in areas underlain by mafic metavolcanic rocks (amphibolite) or granodiorite and identifies areas with potential to act as structural‐lithological trap rocks for pegmatite melts. The identified parts from the integrated 3D inversion modelling in a few candidate areas are then compared to conceptual 3D geological models for Li pegmatite structural and lithological traps in areas with similar geology. The comparison shows interesting correlations between the two ‘end‐member’ melt trapping models and implies possible deeper extension of favourable structures and/or mafic to intermediate rocks (amphibolite and granodiorite) that may host Li pegmatites. We recommend future study for more detailed geological observations in two candidate areas with known mineralization and differing geological settings. Furthermore, acquisition of denser and higher resolution magnetic and electromagnetic data using drones, combined with additional ground gravity measurements, is advised to refine more accurate and higher spatial resolution 3D geomodels of Li pegmatite deposits.