By providing patient-specific advice, clinical decision support systems (CDSSs) are expected to promote the implementation of clinical practice guidelines (CPGs) to improve the quality of care. However, produced as texts, often incomplete and ambiguous, CPGs are difficult to translate into the formal knowledge bases (KBs) of CDSSs. The French National Authority for Health (HAS) decided to update CPGs on the management of type 2 diabetes. This work illustrates the simultaneous development of the text and its formal counterpart in a CDSS named RecosDiab. CPGs were elaborated by a working group according to the guideline development methodology. Textual recommendations were graded, either as evidence-based when evidence existed or as consensus-based when acknowledge by the working group. Knowledge modeling was performed following the steps of de-abstraction, disambiguation, and verification of completeness. This last step generated clinical situations not explicitly mentioned in the text and were graded as expert-based. The resulting KB provides therapeutic advice for 805 clinical situations, among which 2 are graded as evidence-based, 37 are consensus-based, and 766 are expert-based. However, because of the amount of expert-based propositions, the HAS did not endorse the system.