In shrimp farming using biofloc technology it is common to observe a gradual swap in the biofloc colors from green to brown along with shifts in water quality throughout the culture cycle. This change reflects a dominance shift from an autotrophic to a heterotrophic microbial community, resulting mainly from changes in system C:N and N:P ratios. Notwithstanding the ease of the direct analysis of biofloc color, no assessment of its potential as a proxy of water quality has been done so far. Therefore, our aim was to develop a standardized protocol to determine the potential of using the microbial community color index (MCCI) to develop an easy, fast, and low-cost assessment of water quality of intensive marine shrimp farming using biofloc systems. In this study, water quality data were collected from 17 tanks and the biofloc color was obtained from images after filtering with the help of an apparatus built with materials accessible to shrimp producers. We developed and standardized a methodology for reading the average RGB (Red, Green, and Blue) values from pixels of bioflocs images and used this methodology to calculate their average MCCIs. Based on this quantification of colors, it was possible to calculate a correlation matrix among MCCI and several water quality variables. The MCCI was positively correlated with the concentration of carbon, nitrogen, and phosphorus concentration in the bioflocs, total suspended solids, settleable solids and total phosphorus and negatively correlated with water transparency and G (green) values. The MCCI association with important water quality variables was expected for this type of system, in which the dominance by heterotrophic bacteria occurs at the final stages of biofloc succession, during which the system undergoes nutrient accumulation, shifting the bioflocs color from green to brown shades. Thus, it was observed that the water quality variables correlated with the MCCI were those that varied according to the culture stage. Another important result was that artificial images generated from images’ average RGB yielded satisfactory results regarding the similarity to the original images. Therefore, since it is possible to estimate water quality variables from the biofloc colors, this method lays the foundation for the future development of a practical tool (color scale or mobile app) for water quality evaluation. Shrimp farmers can use it to conduct a cheap and fast assessment of water quality of their tanks and take better decisions about critical aspects such as fertilization, water renewal or mechanical removal of excessive concentration of bioflocs.