To study the classification of fracture modes of rocks during the cracking process, uniaxial compression tests were conducted on intact and flawed red sandstone specimens. Meanwhile, both acoustic emission (AE) and digital image correlation (DIC) technologies were adopted to monitor and record the real-time cracking process of the specimens tested. In this study, the interevent time function F(τ) (AE events rate) was utilized to distinguish the transition from microcracking to macrocracking for the tested specimens. An AE parameter analysis method based on two indices of RA (rise time/amplitude) and AF (AE counts/duration) values was performed to classify the different cracking modes during the loading process. The classification results of the cracking modes coincide with the cracking type of macrocracks captured by the photographic system. Moreover, the adequacy of the crack classification was also evaluated by the kernel density estimation (KDE) function, a nonparametric density estimation method. KDE is used as a parametric model to overcome the randomness found in the data set generated by AE testing and can well identify and visualize the high concentration regions of RA and AF values. A continuous increase of RA values (more than 400 ms/v) can serve as an early warning for the ultimate failure of red sandstone. The results of this present investigation can be applied in the health monitoring of rock engineering.