We have developed a new constrained inversion method that is based on a probabilistic approach for resolving crustal structure from regional gravity data. The smoothness of estimated structures is included in the inversion by using a model covariance matrix, and the sparse boundary information obtained from seismic data is incorporated in the inversion by using linear equality constraints. Moreover, constraints on the average anomalous densities expected for different crustal layers are applied instead of using a depth-weighting function. Bathymetric data and sediment thicknesses are included in the inversion by using an a priori model. Using the proposed method, model structures with sharp boundaries can be obtained while the existing boundary information and sparse seismic constraints are honored. We determine through a synthetic example and a real-world example that the proposed constrained inversion method is a valid tool for studying crustal-scale structures.