The Fennoscandian Shield as a part of a large Precambrian basement area is located in northern Europe and hosts economically important mineral deposits including base metals and precious metals. Regional geophysical data such as potential field and magnetotelluric data in combination with other geoscientific data contain information of importance for an understanding of the crustal and upper mantle structure. Knowledge about regional-scale structures is important for an optimized search for mineralisation. In order to investigate in more detail the spatial distribution of regional electrically conductive structures and near-surface mineral deposits, complementary magnetotelluric measurements have been done within the Precambrian Shield in the north-eastern part of the Norrbotten ore province. The potential field data provided by the Geological Survey of Sweden have been included in the current study. Processing of magnetotelluric data was performed using a robust multi-remote reference technique. The dimensionality analysis of the phase tensors indicates complex 3D structures in the area. A 3D crustal model of the electrical conductivity structure was derived based on 3D inversion of the data using the ModEM code. The final inversion 3D resistivity model revealed the presence of strong crustal conductors with the conductance of more than 3000 S at depth of tens of kilometres within a generally resistive crust. A significant part of the middle crust conductors is elongated in directions that coincide with major ductile deformation zones that have been mapped from airborne magnetic data and geological fieldwork. Some of these conductors have near-surface expression where they spatially correlate with the locations of known mineralisation. Processing and 3D inversion of the regional magnetic and gravity field data were performed, and the structural information derived from these data by using an open-source object-oriented package code written in Python called SimPEG. In this study, a new approach is proposed to extract and analyse the correlation between the modelled physical properties and for domain classification. For this, a neural net Self-Organizing Map procedure (SOM) was used for data reduction and simplification. The input data to the SOM analysis contain resistivity, magnetic susceptibility, and density model values for some selected depth levels. The domain classification is discussed with respect to geological boundaries and composition. The classification is furthermore applied for prediction of favourable areas for mineralisation. Based on visual inspection of processed regional gravity and magnetic field data and a SOM analysis performed on higher-order derivatives of the magnetic data, an interpretation of a sinistral fault with 52 km offset is proposed. The fault is oriented N10E and can be traced 250 km from Karesuando at the Swedish-Finish border southwards to the Archaean-Proterozoic boundary marked by the Luleå-Jokkmokk Zone.