Work using the concept of a co-optimization-based metrology hybridization is presented. Hybrid co-optimization involves the combination of data from two or more metrology tools such that the output of each tool is improved by the output of the other tool. Here, the image analysis parameters from a critical dimension scanning electron microscope (CD-SEM) are modulated by the profile information from optical critical dimension (OCD, or scatterometry), while the OCD-extracted profile is concurrently optimized through addition of the CD-SEM CD results. The test vehicle utilized is the 14-nm technology node-based FinFET high-k/interfacial layer (HK/IL) structure. When compared with the nonhybrid approach, the correlation to reference measurements of the HK layer thickness measurement using hybrid co-optimization resulted in an improvement in relative accuracy of about 40% and in from 0.81 to 0.91. The measurement of the IL thickness also shows an improvement with hybrid co-optimization: better matching to the expected conditions as well as data that contain less noise.