Temperature alteration plays special role as one of the most basic climate elements. So inspection of temperature alteration and anticipation has scientific- applied magnitude. In this study inspection of several cases of statistical characteristics of monthly­ average, maximum and minimum temperature and illumination of their alteration method­, temperatures predictability by ANFIS is evaluated­. Applied data is over 288 months during 24 years of statistical period since January of 1987 until December of 2010 through synoptic stations of Pars Abad, Ardebil and Khalkhal. According to equations of data lineal process­, lineal process of temperatures through all of the stations is positive and­ additive­. Lineal process gradient in minimum temperature is more than other­ maximum and average temperature. Less amplitude more variance and standard aviation and­­ data ­predictability is more. According to present article adaptive Neuro – fuzzy inference system mostly has acceptable function through anticipation of monthly minimum, maximum and average temperature in the stations of Ardebil province.