Drug resistance testing significantly improves response to antiretroviral treatment in HIV-1-infected patients, therefore it has recently been implemented into current guidelines for the management of antiretroviral therapy. Knowledge about technologies for measuring drug resistance is important for several reasons: (a) differences exist between different technologies and also between assays based on the same technology; (b) the results of resistance testing are strongly dependent on the reliability and precision of the technology used; and (c) technical aspects have to be considered for a clinically relevant interpretation of drug resistance. The spectrum of genotypic and phenotypic technologies as well as the technical quality is increasing, which shifts the emphasis to the interpretation of resistance profiles. The interpretation is based on the knowledge of drug resistance-associated mutations as well as correlations between genotype and phenotype and clinical response, which are incorporated into rules-based systems. Bioinformatic techniques are used to generate mathematical models for the prediction of drug resistance from genotype. Both approaches are converging toward the prediction of clinical response. Because therapy response is dependent on many additional variables, further efforts are required for the generation of a large clinical database. This will be the basis of a prediction system that will optimize the antiretroviral therapy for each individual patient.