In blockchain networks, the probability of forks, where the chain splits due to simultaneous block discoveries, is a critical factor affecting both performance and security. This paper investigates how the probability distribution of block mining times influences the likelihood of fork occurrences. We develop a formal model to examine the impact of the number of miners, the distribution of their hashing power, and the probabilistic characteristics of block mining times on the fork probability. Our analysis reveals that the block mining time (BMT) distribution, which follows a geometric distribution in Bitcoin, can significantly affect fork rates. We propose an optimization approach to identify BMT distributions that minimize the probability of forks in various network configurations. Our findings suggest that tailored BMT distributions could enhance blockchain protocol design by reducing fork frequency, thus improving consensus reliability and overall network performance. This theoretical study provides insights into the potential customization of block mining processes to achieve more robust and efficient blockchain systems.