This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Events can have different magnitudes, frequencies, and distributions of occurrence. The problem can be worse or the solution better if greater frequencies and magnitudes are presented with aggregated distribution in the production system (Demolin-Leite, 2021, 2024. The Percentage of Importance Indice (% I.I.) based on this triplet to identify loss and solution sources, classifying them according to their importance in terms of loss or income gain, on the productive system (Demolin-Leite, 2021, 2024). The % I.I. can be significant for preserving native areas, avoiding their degradation, assisting the traditional communities, like the quilombolas (rebellious slaves refuge area in the Brazilian colonial period), indigenous, collectors (e.g., fruits), to identify the true loss sources of production in native plants. Thus, with the help of extension researchers, they can plan the best management of these potential pests, making more money, avoiding tree-cut for charcoal production (Demolin-Leite, 2024). This index and its derivations (e.g., non attention level) were obtained using the statistical programs Biodiversity Professional program, version 2 (Krebs, 1989) -for chi-square test -and System for Analysis Statistics and Genetics, version 9.1 (UFV, 2007) -for simple regression analysis -, and also part of the calculations (e.g., maximum estimated production) using an Excel datasheet. However, the transfer of information from the data obtained via the statistical programs mentioned above, as well as the calculations performed using the Excel datasheet, in addition to being labor intensive, could incur mathematical errors due to the volume of equations and data. For this purpose, a package and its manual were developed, via the R program, to perform the statistics and calculations necessary to obtain the %I.I. and its derivations (Demolin-Leite and Azevedo, 2022). This study aimed to demonstrate to use of the R-Package "Importance Indice" (Demolin-Leite and Azevedo, 2022) using adapted published data (simplified) (see Demolin-Leite, 2024) in relation to those obtained with the statistical programs mentioned above. The package is available on Cran's platform (Demolin-Leite and Azevedo, 2022).The equation of the % of Importance Indice (% I.I.) (Demolin-Leite, 2021, 2024) is: % I.I. ={(ks 1 x c 1 x ds 1 )/Σ (ks 1 x c 1 x ds 1 ) + (ks 2 x c 2 x ds 2 ) + (ks n x c n x ds n )}x100, where: