Multivariate statistical techniques were applied to identify the behavior of physicochemical parameters on calorific value in oil samples used in the industrial petrochemical sector of Mamonal in Cartagena de indias, Colombian Caribbean.Initially a physicochemical characterization of the samples was carried out through a principal components analysis, then a cluster analysis to identify similarities between the samples and to have a better description of the samples and finally a multiple regression model is fitted to determine the physicochemical factors that influence In the behavior of the calorific value of the oil samples.The results show that there are different associations between the physicochemical parameters; The cluster analysis yielded 4 groups of oil samples with different physicochemical behaviors and according to the criterion of loss of AIC information in the linear regression model, samples with low sulfur, sodium and ash content and high zinc content, Phosphorus and chlorine contribute to the increase of calorific value in the samples.Keyword-Oil reused, Principal components analysis, Heat power, Physicochemical variables. I. INTRODUCTIONThe demand for treated oils to be used as an energy source would depend on the cost of the cleaned or cleaned oils, the cost of the fuels to be used if mixed and the behavior of the consumers of the new fuel [1,2,3].The treatments applied to the used oils allow, through a degree of cleaning, to increase the percentage of the lubricant base present in the original oil, so that they are suitable for formulation and use [4,5].That is, the raw material will be reused, thus achieving the minimum amount of waste discharged into the medium in liquid form [6,7].Interest in the combustion of waste oils has grown exponentially in recent decades as an important strategy to combat climate change through the production of renewable heat and electricity [8,9].Because of its high heat capacity, the treated oil has great potential to be used as fuel not only for its properties and characteristics, but also for the need to have energy alternatives and safe energy supply, by releasing it from the components that make it a waste Dangerous [9,10].It can be used for combustion in furnaces, boilers, foundries, dryers, heating, plasticizer manufacturing processes and if it is released from all impurities in internal combustion engines; In this last aspect, this work is centered on the use of a calorimetric pump to determine the specific calorific value of a sample, carrying out its combustion in an oxygen atmosphere [11,12].Multivariate analysis techniques are a very useful tool for differentiating groups within a given population based on different criteria [13].For all of the above, it is established as the objective of this research To identify by means of a multiple regression statistical model the physicochemical parameters that influence the calorific value in samples of oil used in the industrial sector; For this a characterization of the samples with respect to said parameters is carried out and in this way to determine which have desirable conditions in terms of a calorific value meaning of use and application.