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Behavioral experiments with infants are generally costly, and developmental scientists often struggle with recruiting participants. Online experiments are an effective approach to address these issues by offering alternative routes to expand sample sizes and access more diverse populations. However, data collection procedures in online experiments have not been sufficiently established. Differences in procedures between laboratory and online experiments can lead to other issues such as decreased data quality and the need for preprocessing. Moreover, data collection platforms for non-English speaking participants remain scarce. This article introduces the Japanese version of Lookit, a platform dedicated to online looking-time experiments for infants. Lookit is integrated into Children Helping Science, a broader platform for online developmental studies operated by the Massachusetts Institute of Technology (Cambridge, MA, USA). In addition, we review the state-of-the-art of automated gaze coding algorithms for infant studies and provide methodological considerations that researchers should consider when conducting online experiments. We hope this article will serve as a starting point for promoting online experiments with young children in Japan and contribute to creating a more robust developmental science.