Abstract The present study clarifies the development of accurate, selective, rapid, sensitive, and economic four spectrophotometric methods for the simultaneous estimation of Atenolol (ATE) and amlodipine besylate (AMB) in their binary mixtures and pharmaceutical products. This combination is widely used in the treatment of cardiovascular disorders. Three multivariate analysis techniques were developed based on the application of calibration prediction (artificial intelligence techniques) includes; Artificial Neural Network (ANN) (method 1), partial least squares (PLS) (method 2), Principal Component Regression (PCR) (method 3), in those methods the ATE and AMB were measured at 238nm and 240nm respectively. The multivariate models are designed using twenty-five mixes as a set of calibration and five mixes as a set of validation. The fourth method depends on the second derivative of ratio spectrum (DR2) as a validation method for all above techniques. The linearity of all methods was observed in the concentration ranges of 0.5- 30.0 µg mL-1 for ATE and 0.25- 28.0 µg mL-1 for AMB. ANOVA test was achieved on the pharmaceutical sample at a 95% confidence level for paralleling ANN, PLS, PCR, and DR2. The Established techniques have been used to separate laboratory prepared mixes of ATE and AMB. These processes have been evaluated conferring to the ICH guidelines with regard to linearity, accuracy, precision, selectivity, and specificity and can be used for sequence ATE and AMB quality control analysis in their dosage forms.