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Abstract High-resolution millimeter-wave imaging (HR-MMWI), with its high discrimination contrast and sufficient penetration depth, can potentially provide affordable tissue diagnostic information noninvasively. In this study, we evaluate the application of a real-time system of HR-MMWI for in-vivo skin cancer diagnosis. 136 benign and malignant skin lesions from 71 patients, including melanoma, basal cell carcinoma, squamous cell carcinoma, actinic keratosis, melanocytic nevi, angiokeratoma, dermatofibroma, solar lentigo, and seborrheic keratosis were measured. Lesions were classified using a 3-D principal component analysis followed by five classifiers including linear discriminant analysis (LDA), K-nearest neighbor (KNN) with different K-values, linear and Gaussian support vector machine (LSVM and GSVM) with different margin factors, and multilayer perception (MLP). Our results suggested that the best classification was achieved by using five PCA components followed by MLP with 97% sensitivity and 98% specificity. Our findings establish that real-time millimeter-wave imaging can be used to distinguish malignant tissues from benign skin lesions with high diagnostic accuracy comparable with clinical examination and other methods.