Asymptotic behavior and halting probability of Turing Machines

Through a straightforward Bayesian approach we show that under some general conditions, a maximum running time, namely the number of discrete steps performed by a computer program during its execution, can be defined such that the probability that such a program will halt after that time is smaller than any arbitrary fixed value. Consistency with known results and consequences are also discussed.