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Cloud model covers the randomness gap in fuzzy logic model and represents the uncertainty transformation between two different concepts. First concept is the linguistic term that represent the qualitative mean. While the second is the crisp term which represent the quantitative mean. The proposed work presents promising model which combines cloud model, fuzzy time series, and Heikin-Ashi candlestick to predict and confirm accurate stock trend. The model solves several challenging such as: nonlinearity, uncertainty and noises in stock market trend. Heikin-Ashi Candlesticks are an extended branch of Japanese candlesticks, such candlestick filters out stock noise and effort to highlight the trend. Heikin-Ashi Candlestick is constructed by calculating averages of the previous and current period prices. Cloud model handle the ambiguous and uncertainty in the Japanese candlestick definitions (qualitative …