Complementary Metal Oxide Semiconductor (CMOS) Image Sensors (CISs) emerged in the past decade due to the advantages of lower power consumption and easier integration with CMOS integrated circuits (ICs) in comparison to the traditional Charged Coupled Devices (CCD). The CIS has further become the major optical component of embedded camera modules of notebook computers in the internet era. Albeit important, embedded camera module vendors usually have difficulties for selecting a suitable CIS to fulml both goals, time to market and profitability. Thus, this research intends to develop a fuzzy multiple criteria decision making (FMCDM) method based framework which can assist the embedded camera module vendors make timely and correct decisions. At first, criteria for evaluating the CIS will first be summarized by literature review and then evaluated by using the brain storming method. Weights versus each criterion will be derived by using the Analytic Hierarchical Process (AHP). For each criterion, the linguistic variable based performance scores versus each alternative will be evaluated and transferred to crisp numbers by using the triangular function. Finally, evaluation results toward each alternative will be derived by using the Simple Added Weighting (SAW) method. An empirical study will demonstrate the feasibility of this proposed FMCDM by a real world notebook (NB) computer built-in camera module sensor selection in a Taiwan based optical device manufacturer. Further, the result can serve as a basis for built-in camera module vendors' selections of CISs.