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The aim of this work was to develop an eco-friendly adsorbent to remove the lead ions from aqueous solutions. The present study uses the artificial neural network (ANN) and genetic algorithm (GA) as tools for simulation and optimization of the lead ions removal from aqueous solutions using intercalated tartrate-Mg–Al layered double hydroxides as an adsorbent. A multi-layer ANN model trained with Levenberg–Marquardt (LM) algorithm was incorporated for developing a predictive model. The input variables of the model were time, solution pH, adsorbent dosage, and lead ion concentration, while the percentage of lead ions removal was the output. The performance of the ANN model was determined and showed the efficiency of the model to predict the percentage of lead ions removal accurately with determination coefficient (R²) of 0.99986. The developed ANN model was then used with GA to optimize the …