Water is one of the most vital constituents in plants. In this research, for an estimation of leaf moisture content, the variation of capacitance was employed. The variations were measured via designed and manufactured capacitive sensors. The objective of the research was to estimate leaf moisture content by measuring its capacitance for five agronomic crops. Experiments for measuring leaf capacitance were performed on maize, sorghum, capsular bean, white bean and sunflower at two frequencies of: 100 kHz and 1 MHz. The results showed that in all cases the best fitted curve for variations of the capacitance in relation to leaf moisture percentage was in the form of an exponential function namely: y= aebx (where y is capacitance, x is leaf moisture content, a is the linear coefficient, and b is the exponential coefficient). Parameters a and b for different plants of each crop and each frequency were not significantly different at 1% probability level. However, these coefficients were significantly different among different crops. Coefficients of determination were higher at 100 kHz than at 1 MHz. It was also observed that the higher the leaf moisture the more the data points scattered around the best-fit line, although the scattering was more uniform at 1 MHz.