Recent estimates indicate that dark matter represents 85% of the total matter in the Universe. Its presence, so far, is manifested through gravitational effects, where one of its most concrete evidence can be verified through the rotation curves of disk galaxies. Motivated to understand how dark matter is distributed in galaxies like our own, we define a sample of Milky Way (MW) analog galaxies. Our sample is derived from the S4G and VIVA surveys, which are the most complete surveys regarding stellar mass characterization and atomic hydrogen gas (HI) distribution in nearby galaxies, respectively. The mid-infrared imaging at 3.6 and 4.5μm of the S4G survey is the best single band tracer of the stellar mass, allowing us to make a careful analysis of the baryonic mass distribution in our sample. On the other hand, using the data cubes of the HI distribution from the VIVA survey allows us to map the distribution of the dark matter component. Our sample is composed of 6 MW analogs, defined as such based on the maximum rotation velocity of the HI gas and morphological type similar to the Milky Way. This proves to be efficient as we limit ourselves to objects that present physical characteristics similar to the Milky Way galaxy. For each object present in the sample, we constructed rotation curves from the intensity and velocity maps of the HI derived through the VIVA survey data cubes. In order to disentangle the contributions due to baryonic and dark matter, we did the characterization of the stellar mass distribution based on the S4G imaging. Finally, we develop an analytical model for dark matter distribution and decompose the rotation curves into the different mass contributions. The model is guided by parameters extracted from the decomposition of stellar mass into different components of the internal structure of galaxies (e.g. bulge, disk and halo), ensuring a reliable profile of the mass distribution. This work allows us to generate maps of dark matter distribution in Milky Way analog galaxies, opening the possibility of constructing a set of realistic variations of dark matter profiles in our own galaxy.