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Mizo is a tone language of the Kuki-Chin subfamily of the Tibeto-Burman language family. It is a under-studied language and not much resources are available for the language. Moreover, it is a tone language with four different tones, namely, high, low, falling and rising. While designing a speech recognition system it becomes imperative that tonal variations are taken into consideration. Hence, a tone detection method for Mizo is designed using quantitative analysis of acoustic features of Mizo tones. Traditional methods of modelling requires large data for training. As such database is not available for Mizo, we relied only on the slope and height for detecting Mizo tones. In this method, we first converted the pitch values to z-score values. Then the z-score values are fitted to a line. An analysis is made on the distributions of the variance of the pitch contour, represented by z-scores, to classify the tone as High/Low or Falling/Rising. Then depending on the slope and height values the tone is further classified into High or Low and Rising or Falling, respectively.