The time‐lagged correlations of monthly precipitation in Myanmar and the Indochina Peninsula (ICP) with several climate indices were investigated by using Global Precipitation Climatology Centre dataset after checking its quality with rain‐gauge data. The results showed significant time‐lagged correlations of several climate indices related to El Niño‐Southern Oscillation and El Niño Modoki with precipitation anomalies in Southern Myanmar during pre‐monsoon (April) and post‐monsoon (October) months. Composite analysis of extremes and Empirical Orthogonal Function (EOF) analysis on precipitation variations over the whole ICP for these 2 months were carried out. The analyses showed a good association between precipitation in Southern Myanmar and a large‐scale precipitation structure that affects the Southern Myanmar and ICP simultaneously during these 2 months. An analysis of moisture flux over a wide area of ICP, including the surrounding seas, showed that the regressed variability of its convergence with the first principal component (PC1) of EOF analysis on precipitation over the whole ICP is statistically significant over the wide area from the Bay of Bengal to Southern ICP and South China Sea for the 2 months. The significant time‐lagged correlations were confirmed by regressing sea surface temperature (SST) in the Pacific and Indian Oceans and 850‐hPa zonal wind (U850) upon the PC1. We propose an area‐averaged SST, U850, or the combination of these variables at each corresponding best location in the equatorial region to the highest correlation searched in this study as a good predictor for long‐range statistical prediction of monthly precipitation in the southern part of ICP, particularly for the pre‐monsoon month. Using a linear model and the proposed predictors, we demonstrate a successful hindcast in predicting the pre‐monsoon and post‐monsoon precipitation in the southern part of ICP (south of 20 N) up to 6 and 3 months ahead, respectively.