Abstarct: The Kivi is located in Ardabil (northwestern province of Iran) which is one of the potential areas for mextallic elements exploration. Geological, geochemical and geostatistical studies, remote sensing, airborne geophysics and geostructure are useful tools for trying to explore minerals and especially in this region. The main purpose of this thesis is to process data (stream sediment samples, satellite images, magnetic airborne geophysical surveys, regional faults and geological studies) to identify mextallic mineralization anomalies. Initially, the geochemical data of the stream sediments were modified using the Dorffel method. Then, univariate statistical processing was performed and resulted in the selection of titanium and zinc as the elements with the best contrast. The relationship between the elements was investigated using correlation analysis and hierarchical clustering. According to the results, it was found that titanium and zinc play an important role in mineralization of the region. Principal component analysis (PCA) was performed to select the mineralization index component related to these elements. The selected component was determined on the geological map of the drawing area as well as the geochemical threshold of the anomalous samples using probability and fractal concentration-area (C-V) diagrams. Titanium and zinc were analysed by and linear discriminant analysis (LDA) using the thresholds. Lithological units and patterns of change were detected by remote sensing (methods: BR, DSPCA and MNF). Using magnetic aerial surveys, geophysical modeling data and selected high probability geochemical area in these studies were also potentially explored. By looking at the map of faults in the region and the existence of kivi faults in the identified area, the possibility of controlling this mineralization by faults can be added to the exploration keys. The results of geostatistical studies on geochemical data, remote sensing, airborne geophysics, geology and structure, identified Ti and Zn anomalies in the eastern part of the study area. According to this study, Ti and Zn have been identified as good interceptors for further research in the Kivi region. According to this important reason, the behavior of two elements along with their geographical location were studied by k-means clustering method and using them as another exploratory key, the amount of titanium in the region with artificial neural network and regression was predicted. The artificial nerve provided more accurate answers.