The wettability of reservoir rocks influences multi-phase fluid flow and rock physics measurements. This impacts the relative permeability, recovery factor, choice of enhanced oil recovery method, and reservoir characterization. Wettability can be assessed using contact angle measurements and the imbibition-based Amott and USBM indices. These methods require preserved core samples, may be time consuming, and cannot be applied for in-situ conditions. Another method to assess wettability is the interpretation of geophysical measurements such as electrical resistivity and Nuclear Magnetic Resonance (NMR). One advantage of geophysical measurements is their applicability for laboratory and in-situ borehole environments. Furthermore, they are quick, non-invasive measurements, and can provide physics-based wettability estimates in near-real-time and in-situ conditions. This thesis provides experimental verification for physics-based assessments of wettability from the interpretation of resistivity and NMR measurements as well as a new workflow for joint interpretation of resistivity and NMR measurements. Recently, analytically-derived resistivity and an NMR-based wettability index rock physics models were introduced and verified using pore-scale simulations. The work presented in this thesis verifies their applicability to core-scale measurements. Additionally, a resistivity-based wettability index is introduced using the fraction of hydrocarbon-wet grains. This index is experimentally verified with Amott and USBM wettability indices. Given reliable estimates of water saturation and the pore-geometry-related model parameters, this resistivity model provides wettability assessment from resistivity measurements with minimal calibration efforts. Moreover, a new method for interpretation of 2D NMR maps is introduced to simultaneously estimate water saturation and wettability. Finally, this thesis introduces an integrated inversion workflow for joint interpretation of resistivity and NMR measurements to simultaneously estimate wettability and water saturation. This method has an average relative error of 11% between the multi-physics- and gravimetric-based water saturation estimates, and an average absolute difference of 0.15 between multi-physics- and Amott wettability indices. This workflow uses physically-meaningful inputs and eliminates the non-uniqueness of water saturation and wettability estimates obtained from independent application of resistivity and NMR models. These outcomes are promising for improved interpretation of resistivity and NMR measurements, particularly in complex, mixed-wet and hydrocarbon-wet formations