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tokens: emission produced by electrons spiralling on the magnetic field lines in a dipolar magnetic field. From the literature (e.g. Svestka 1981 ; Bastian et al. 1998 ), it is assumed that in the radio range the emission comes from the non-thermal electrons that are accelerated in the corona and then propagate down to the foot-points of the loops with a commonly accepted power-law distribution in energy. Nevertheless, when taking into account the comparison between radio and hard X-ray observations, our 3D magnetic loop radio modelling agrees reasonably well with the literature in relation to the location and sizes of the radio source. The ambient plasma is supposed to be a quiescent background with some temperature and density profiles. It is widely known that the radio emission emanates from the chromosphere to corona where the electrons are trapped due to magnetic mirroring. Thus, the number density of non-thermal electrons refers to different locations in the loop and different distribution of trapped or precipitating particles, from which it follows that a detailed determination of the emitting region parameters in microwaves and hard X-rays is important. We present an alternative approach to the time-consuming process to calculate a non-homogeneous model – each time one is needed for a flare analysis – by providing a data base of pre-calculated models constrained by some statistical properties of a large sample of Nobeyama observations. We know that this data base is still limited in terms of the wide range of parameter combinations needed to calculate the gyrosynchrotron emission to describe all possible scenarios of flares in the microwave. We statistically analysed 10 important parameters, that in general cannot be directly observed, to explain a flare as shown in Fig. 6 . We found that 8 out of 10 parameters in the simulations were recovered with a relative error ≤20 per cent on average. We consider this result an improvement for flare analysis in terms of the time consumed with the calculations. Although the data base was produced using equally distributed parameters from the lower to upper limits, the geometric bias discussed in Section 6.1 results in differences in the distributions of geometry, magnetic field, and energy parameters. In the energy parameters, the observed solar bursts show preferences for lower non-thermal electron density and a slight preference for higher densities for the limits used here. The magnetic field distribution shows some preference for higher values than the centre of the data base range we used. We also noted some shift in the distribution for loop-top events. In general, the geometric parameter distribution shows a tendency for bigger loops. Differences between individual solutions are mainly due to the degeneracy of results with quite similar χ 2 in the dominion of 10 parameters. This is the reason that we preferred the averaged solution weighted by the χ 2 . Table 3 shows the best parameters inferred