Leafy vegetable cultivation, such as mustard greens (Brassica juncea) and celery (Apium graveolens), frequently encounters constraints due to unstable microclimatic conditions in open-field environments, including fluctuations in temperature and humidity as well as pest attacks. These conditions lead to significant declines in crop productivity and yield quality. This study aims to analyze the effectiveness and performance of an Internet of Things (IoT) based Smart Greenhouse prototype in optimizing microclimate control and measurably enhancing plant growth. This research employed an experimental approach using an engineering-based experimental design, encompassing system design, sensor calibration, functional testing, and plant growth trials. The experimental subjects consisted of 20 plants. Data were collected through direct observation, automated sensor logging, and plant growth documentation, utilizing validated and reliable instruments including DHT22, BH1750, YL-69, and DS3231 RTC sensors, which were tested for measurement accuracy and consistency. Data analysis was conducted using descriptive quantitative analysis and comparative analysis of mean growth between experimental groups. The results indicate that the Smart Greenhouse system successfully maintained temperature, humidity, and light intensity within optimal ranges, with sensor accuracy exceeding 95%. Furthermore, mustard greens exhibited a 28% higher growth rate compared to open-field cultivation, while celery demonstrated a more moderate improvement. The study concludes that IoT-based microclimate control is effective in enhancing horticultural crop productivity through precise and automated environmental regulation.