Non-nucleoside reverse transcriptase Inhibitors (NNRTIs) are antiretroviral drugs that bind to an allosteric site in HIV reverse transcriptase (RT). NNRTIs are often associated with treatment failure due to emergence of resistance mutations. Rilpivirine (RPV) and etravirine (ETV) were designed as a flexible diarylpyrimidines (DAPYs) that can adapt to multiple mutations in the NNRTI binding site. We have established a computational, structure-based method to predict resistance mutations to NNRTIs and similar compounds in development. The objective of this study is to examine this approach for 2 types of NNRTIs: DAPY and non-DAPY. RPV and ETV were selected for the analysis and resistance prediction of DAPY NNRTIs. Doravirine (DOR) was selected as a non-DAPY NNRTI for this study. In our approach, we employed molecular docking and residue scanning to predict resistance to both NNRTIs. Results from residue scanning predicted that the K101 P mutation conferred high level resistance to RPV and ETV. DOR remained susceptible to the K101 P mutation. These predicted results were further validated through structural analysis, molecular dynamics, and an enzymatic reverse transcription assay. Our results indicate that stability and affinity changes in RT in complex with NNRTIs are accurate predictors of drug resistance. As this is a proof of concept study, we believe that our computational and structure-based approach may be used to predict resistance to diverse inhibitors in development.