In order to explore new options to optimize the low-grade copper ore bioleaching process, it is important to understand the kinetics of microbial oxidation at industrial level. This work studies the changes of iron and sulfur oxidation rates of microbial communities in solution from an industrial low grade copper bioleaching heap process at Escondida Mine in Chile. Pregnant leach solution (PLS) samples were analyzed periodically to determine physico-chemical parameters. The total numbers of the different microorganism species in industrial samples were determined by Real Time PCR. In addition, Most Probable Number assays (MPN) were performed for iron and sulfur oxidizing microorganisms. Kinetics incubation tests of PLS in the presence of iron or sulfur were performed to study the iron and sulfur oxidation, in total, 102 oxidation profile tests were obtained. Based on the oxidation profiles obtained, the tests were divided into four groups, labeled as fast, normal, stepped shape, and incomplete. The grouping system was established by considering oxidation time and rates, during the initial oxidation stages and accounted for any lag phase. A data mining technique, called decision trees was used to analyze the data and to generate rules that represented patterns in the data. Strong correlations were found between the predominant microorganisms and the behavior of the oxidation tests. Preliminary results indicate that the magnitude order of MPN of the iron oxidizing microorganisms is an important factor in the microbial oxidizing activity, followed by the predominant specie within the microbial population, PLS temperature and Eh.