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The sharp rise in temperature has increased the frequency, intensity, duration, and timing of heat waves (HWs) over different regions of the world. Due to climate change, the China–Pakistan Economic Corridor (CPEC) is one of the highly vulnerable regions to HWs and needs comprehensive research studies to investigate the HW phenomenon in the region. This study analyzed the spatial and temporal changes in the daytime and nighttime HW characteristics based on multiple indices over the CPEC region. We used daily maximum and minimum temperatures (hereafter Tmax and Tmin) of 48 meteorological stations for the time period of 1980–2016. The non-parametric modified Mann–Kendall, Theil–Sen’s test, least square method, student t-test, and chi-square goodness-of-fit test techniques were used to analyze the long-term spatiotemporal changes in the daytime and nighttime HW characteristics. The results of the study show that the number of annual daytime/nighttime HW events, annual sum of participating daytime/nighttime HW days, the average length of annual daytime/nighttime HW events, duration of the longest annual daytime/nighttime HW event, the average magnitude of all annual daytime/nighttime HW events, amplitude of the hottest annual daytime/nighttime HW event, and the ending date of annual last daytime/nighttime HW event exhibited significant increasing trends at the rate of 0.78/1.43 events decade−1, 10/11.82, 2/1.74, 2.16/1.52 days decade−1, 0.40/0.59, 0.24/0.73 °C decade−1, and 12.29/10 days decade−1, respectively. Despite all, the onset date of the annual first daytime/nighttime HW event has shown a significant decreasing trend of − 5.71/− 5 days decade−1. The obvious positive trend of HW behaviors indicates that the country has experienced more frequent, stronger, more intense, and longer HWs during the study period. The spatial pattern of the trend indicates that the southern, central and eastern parts of Pakistan exhibited prominent and consistent HW activities, while the northwestern mountainous regions showed high spatial variability with some stations exhibited decreasing trends in HW indices. The findings of this study will be a base for the projection and mitigation of HWs in the region. Based on the study findings, we recommend that the mechanism of HW and its natural and anthropogenic drivers should be thoroughly investigated over the study region.