The role of decision models in supporting automated clinical practice guideline development is gaining importance in recent years. Constructing decision models from scratch, however, is laborious, time-consuming, and knowledge-intensive. This paper presents a new practical methodology to facilitate effective dynamic decision model construction for clinical practice guideline development, updating and customization. The proposed approach uses existing paper-based guidelines in sharable formats as the main information sources, characterizes the information inherent in the decision models and the clinical practice guidelines, establishes the relevant correspondences, reduces the effort needed in decision model construction, and increases the reusability and flexibility of the knowledge captured in the resulting guidelines.