The challenging task of managing business processes has become an even more complex endeavor as companies are required to sustain flexible and agile business practices. Process management research has proposed numerous ways of accommodating for this need for flexibility. The declarative process modeling paradigm, with its shifts towards a constraint-based way of approaching process behavior, is a prime example. The downside of numerous languages covered by this paradigm, however, is the complex nature of their constraints, as well as their interactions. This thesis offers numerous solutions to overcome these impediments for improved usability of declarative process models. In the first part, an overview is given of the current landscape of declarative process modeling, extended with the formal basis for the remainder of the text. A conversion of a common body of process constraints into a procedural variant is provided as well. In the second part, an approach to reveal (hidden) dependencies among constraints in declarative process models is proposed. This contribution allows users to better grasp the full behavior of such models, for implicit connections are explicited and added as an extra layer of annotation on top of the current representation. The effectiveness and usefulness of the approach is illustrated in a user study and is also used for constructing a complexity measure for constraint-based models. In the third part, the comparison with the procedural process modeling paradigm is made. Analogies and intricacies to both approaches are leveraged towards modeling in a mixed-paradigm fashion, as well as towards achieving better automated process discovery results. The findings are further extended by an approach for checking mixed-paradigm models for inconsistencies, and a conformance checking approach for assessing mixed-paradigm mining results. Finally, the last part provides an outlook for future work. All examples are elaborated in the Declare framework, which provides a widely-supported language and body of tools.