The main objective of this research study was to develop a mathematical model to predict the score that indicates coffee’s sensory quality. To develop the model, the study examined 11 physicochemical parameters, 34 coffee samples, and the judging scores from a 12 cupping judge panel. A multiple regression analysis was performed to determine the relationship between physicochemical parameters and sensory quality to obtain the square of the adjusted correlation coefficient, the coefficients for each parameter within the model, and their p-values. The results show that the parameters 4-caffeoylquinic acid (4-CQA), pH, color, density, and acidity, have a negative influence on sensory quality. The parameters 3-caffeoylquinic acid (3-CQA), acid 5-caffeoilquinic (5-CQA), humidity, Brix, and caffeine have a positive influence on sensory quality. In addition, the parameters 3-CQA, 4-CQA, and pH showed the lowest p values. It is concluded that the model developed here allows estimating the proper range required to score a coffee batch.