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OBJECTIVE: A systematization for an anthropometric infantile evaluation is proposed, employing the software Epi Info, version 6.0, considering the collective and individual approaches, as well as the degree and type of malnutrition. METHODS: The software Epi Info, sponsored by the World Health Organization, provides an infantile nutritional evaluation, which is based on three anthropometric indicators: weight-for-age, height-for-age and weight-for-height. In order to quantify the observed data of each individual, three scales can be used. Among them, the Z score, which discriminates more efficiently the severe cases, is employed as a first choice. The reference pattern of the NCHS is used. Many cutoff points between eutrophy and malnutrition can be chosen, but the -2 Z score is the most employed. The child can be classified in three diagnostic categories: stunting, for height-for- age deficits; wasting, for weight-for-height deficits; underweight, for weight-for-age deficits. Besides this, in a collective approach, the Epi Info software calculates the proportion of individuals in each populational group which have their anthropometric data deviated from the reference curve, constituting the percentage of observed abnormality (called standardized prevalence). RESULTS: In this paper, in which the analysis of a data file is presented as an example, the organization of the information provided by Epi Info is proposed, with the characteristics described below. In order to increase the diagnostic sensitivity, the collective approach is valued. Concerning the type of malnutrition, the English term "stunting" is substituted by "chronic malnutrition", "wasting" by "acute malnutrition" and "underweight" by "isolated weight deficit". Concerning the degree of malnutrition, the -2 and -3 Z scores are employed as cutoffs in order to define, respectively, a threshold between the moderate and severe forms. CONCLUSIONS: The proposed approach takes into account the identification of all forms of malnutrition, from the mildest to the most severe cases, takes into consideration both height and weight deficits and if the process is acute or chronic. Therefore, it is a tool for organizing data available with the use of the computer.