Karat Killer: Machine Learning Gold EA for Verified MT5 Trading Performance

In this Karat Killer review for 2026 I present a performance analysis based on live account verification, walk-forward testing, and out-of-sample robustness checks. Karat Killer stands apart from many retail gold expert advisors because it deploys a multi-model machine learning ensemble through ONNX Runtime, replacing recycled indicators with statistically driven signals. The 2026 performance figures discussed here derive from verified XAUUSD trading that emphasizes expectancy, win rate, and drawdown control rather than optimistic in-sample curves, and this analysis prioritizes metrics over marketing claims. Karat Killer is developed by BLODSALGO LIMITED for the MT5 environment and uses multiple algorithmic components to classify market regimes, weigh model outputs, and execute trades based on consensus signals. The algorithm performs best in trending but moderately volatile conditions where feature patterns are stable; it reduces position sizes when volatility spikes and applies rolling stops to protect equity. Risk management is explicit: fixed fractional sizing, maximum open trades, and strict risk-per-trade limits. Expected performance characteristics include medium trade frequency, positive expectancy over large sample sizes, and drawdowns that are controlled but nonzero. As with any ML-driven system, Karat Killer requires proper forward testing, broker compatibility checks, and realistic expectations about periodic underperformance during regime shifts.