The objective of this meta-analysis was to evaluate the performance of the Gene Expression Classifier (GEC) and ThyroSeq v2 (ThyroSeq) in the preoperative diagnosis of thyroid nodules with indeterminate fine-needle aspiration biopsy results. We searched literature databases from January 2001 to April 2018. The bivariate model analysis was performed to estimate pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), positive predictive value (PPV), and negative predictive value (NPV). Pooled data from 1086 nodules with histopathologic confirmation from 16 GEC studies enabled calculation of diagnostic parameters (95% confidence interval): sensitivity 98% (96-99%), specificity 12% (8-20%), PPV 45% (37-53%), and NPV 91% (85-96%). Pooled data from five ThyroSeq studies assessing 459 nodules showed sensitivity of 84% (74-91%), specificity 78% (50-92%), PPV 58% (31-81%), and NPV 93% (89-97%). When both tools were compared, GEC had a significantly higher sensitivity (p = 0.003), while ThyroSeq had a significantly higher specificity (p < 0.001) and accuracy (p = 0.015).