FT-MIR spectroscopy coupled to chemometrics can be an alternative technique to conventional methods to determine the chemical composition of berries such as strawberry. This study developed chemometric models based on FT-MIR spectroscopy to identify strawberry cultivars at seven stages of ripening and quantify the main attributes involved in sensory quality of strawberry fruits (total soluble solids, total acidity, reducing sugars, pH) and the main bioactive compounds involved in antioxidant capacities (ascorbic acid, phenolics, flavonoids, anthocyanins). PCR, PLS1 and PLS2 algorithms were used to develop the prediction models. PLS1 algorithm developed excellent predictions with Rc2 -greater than 0.90. SIMCA model identified the cultivars with 99% confidence. Unlike conventional methods, FT-MIR allowed us to analyze simultaneously the attributes of quality, bioactive compounds, and antioxidant capacity of strawberries fruits in a fast and reliable way without the use of reagents and/or solvents, which considerably reduces the time and cost of the analyzes.