目前國內在工程營造綜合險（Contractors’ All-Risk Insurance，CAR）保費之估算，大都依據規模相似之保險經驗與資料，對其投保金額進行『粗估』或『概算』而得。近年來工程出險機率提升，導致國內外保險公司對於工程保險保費率之提升，致使國內工程建設成本增加，且保險專業估算人員受限於對工程特性之了解，其所估計之工程保費亦難以真實反應工程之風險程度。 本研究嘗試以案例式推理（Case-Based Reasoning, CBR）之技術，由案例表示過去之知識與經驗，以解決估算作業經驗傳承不易之問題。本研究以過去367個實際工程投保案例為基礎，建立一適用於一般隧道工程之營造綜合險之投保費用及自負額經驗決策支援系統（Decision Support System, DSS）。此系統輸入之參數為工程內容、工程形式、施工地點、營造工程損失險保費結構、營造工程第三人意外責任險保費結構；而其輸出之結果為最相似前『三例』營造綜合險保險案例以及其推估系統建議保險費率。 本研究開發之隧道工程營造綜合險保險費率推估決策支援雛形系統，其建議之保險費準確率達百分之七十，證明以案例式推理技術推估營造綜合保險保費為一可行方式。本系統可輔助新進人員、業主或保險業者快速規劃保險費率，進而降低工程保險成本。 The premium of a Contractors’ All-Risks Insurance (CAR) is usually estimated by an experienced estimators based on similar past cases. However, arising accident rates lead insurance companies to higher premiums that increase the costs of construction projects. In addition, the higher premiums are not accurately reflecting the level of construction risks due to the estimator’s limited professional knowledge in construction. This research attempts to solve the problem of premium estimation by employing a Case-Based Reasoning (CBR) technique into a Decision Support System (DSS) that comprises of 367 past insurance cases in tunnel construction. The input to the system is a set of properties regarding CAR insurance of the construction project; including project size, location, type, construction firm, and insurance structures of material damage and third party liability. The output of the system is a set of most similar cases retrieved from the case base. A proposed premium is also provided by this system. This developed system is tested against 20 real tunnel projects and an accuracy rate up to 70% in estimating insurance premiums has been obtained; thus it proves that the CBR technique is very helpful in estimating the CAR premiums. This developed system can serve as a useful tool in assisting the owner, insurance companies, and new staff members related to tunnel construction projects to quickly perform accurate premium estimations.