A number of human biomonitoring (HBM) studies have presented data on exposure to hexavalent chromium [Cr(VI)] and cadmium (Cd), but comparatively few include results on effect biomarkers. The latter are needed to identify associations between exposure and adverse outcomes (AOs) in order to assess public health implications. To support improved derivation of EU regulation and policy making, it is of great importance to identify the most reliable effect biomarkers for these heavy metals that can be used in HBM studies. In the framework of the Human Biomonitoring for Europe (HBM4EU) initiative, our study aim was to identify effect biomarkers linking Cr(VI) and Cd exposure to selected AOs including cancer, immunotoxicity, oxidative stress, and omics/epigenetics. A comprehensive PubMed search identified recent HBM studies, in which effect biomarkers were examined. Validity and applicability of the markers in HBM studies are discussed. The most frequently analysed effect biomarkers regarding Cr(VI) exposure and its association with cancer were those indicating oxidative stress (e.g., 8-hydroxy-2'-deoxyguanosine (8-OHdG), malondialdehyde (MDA), glutathione (GSH)) and DNA or chromosomal damage (comet and micronucleus assays). With respect to Cd and to some extent Cr, β-2-microglobulin (B2-MG) and N-acetyl-β-D-glucosaminidase (NAG) are well-established, sensitive, and the most common effect biomarkers to relate Cd or Cr exposure to renal tubular dysfunction. Neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule (KIM)-1 could serve as sensitive biomarkers of acute kidney injury in response to both metals, but need further investigation in HBM studies. Omics-based biomarkers, i.e., changes in the (epi-)genome, transcriptome, proteome, and metabolome associated with Cr and/or Cd exposure, are promising effect biomarkers, but more HBM data are needed to confirm their significance. The combination of established effect markers and omics biomarkers may represent the strongest approach, especially if based on knowledge of mechanistic principles. To this aim, also mechanistic data were collected to provide guidance on the use of more sensitive and specific effect biomarkers. This also led to the identification of knowledge gaps relevant to the direction of future research.