The genus Dalbergia contains many valuable timber species threatened by illegal logging and deforestation, but knowledge on distributions and threats is often limited and accurate species identification difficult. The aim of this study was to apply DNA barcoding methods to support conservation efforts of Dalbergia species in Indochina. We used the recommended rbcL, matK and ITS barcoding markers on 95 samples covering 31 species of Dalbergia, and tested their discrimination ability with both traditional distance-based as well as different model-based machine learning methods. We specifically tested whether the markers could be used to solve taxonomic confusion concerning the timber species Dalbergia oliveri, and to identify the CITES-listed Dalbergia cochinchinensis. We also applied the barcoding markers to 14 samples of unknown identity. In general, we found that the barcoding markers discriminated among Dalbergia species with high accuracy. We found that ITS yielded the single highest discrimination rate (100%), but due to difficulties in obtaining high-quality sequences from degraded material, the better overall choice for Dalbergia seems to be the standard rbcL+matK barcode, as this yielded discrimination rates close to 90% and amplified well. The distance-based method TaxonDNA showed the highest identification rates overall, although a more complete specimen sampling is needed to conclude on the best analytic method. We found strong support for a monophyletic Dalbergia oliveri and encourage that this name is used consistently in Indochina. The CITES-listed Dalbergia cochinchinensis was successfully identified, and a species-specific assay can be developed from the data generated in this study for the identification of illegally traded timber. We suggest that the use of DNA barcoding is integrated into the work flow during floristic studies and at national herbaria in the region, as this could significantly increase the number of identified specimens and improve knowledge about species distributions.